From pazzani@ics.uci.edu Wed Mar 1 03:29:39 1995 Received: from cs.wisc.edu by sea.cs.wisc.edu; Wed, 1 Mar 95 03:29:31 -0600; AA04521 Received: from ics.uci.edu by cs.wisc.edu; Wed, 1 Mar 95 03:29:16 -0600 Received: from ics.uci.edu by q2.ics.uci.edu id aa00971; 28 Feb 95 22:33 PST To: ML-LIST:; Subject: Machine Learning List: Vol. 7, No. 4 Reply-To: ml@ics.uci.edu Date: Tue, 28 Feb 1995 21:47:05 -0800 From: Michael Pazzani Message-Id: <9502282233.aa00971@q2.ics.uci.edu> Machine Learning List: Vol. 7, No. 4 Tuesday, February 28, 1995 Contents: Regal MACHINE LEARNING SOFTWARE AVAILABLE `soft' classification Special AI Review journal issue on Lazy Learning Question on t test conservation of generalization Announcement of a Post-Doctoral Position NEW BOOK by Kluwer: Concept Formation and Knowledge Revision RL papers avai GP-96 Call For Papers KDD95: Final Call for Papers GA conference registration info CFP-ML95-PbD Workshop Welcome to ECML-95 ECML-95 CFP: "Relevance" issue of "Artificial Intelligence" MaxEnt95 NIPS*95 Call for Papers NIPS*95 Call for Workshop Proposals Workshop on Data Engineering for Inductive Learning The Machine Learning List is moderated. Contributions should be relevant to the scientific study of machine learning. Mail contributions to ml@ics.uci.edu. Mail requests to be added or deleted to ml-request@ics.uci.edu. Back issues may be FTP'd from ics.uci.edu in pub/ml-list/V/ or N.Z where X and N are the volume and number of the issue; ID: anonymous PASSWORD: URL- http://www.ics.uci.edu/AI/ML/Machine-Learning.html ---------------------------------------------------------------------- Date: Sat, 11 Feb 95 11:38:10 +0100 From: Attilio Giordana Subject: Regal The program REGAL 3.0 for learning relations using a genetic Algorithms is now available on the 'www' server: http://www.di.unito.it in the section: Machine Learning/Genetic Algorithm Group The same program is also available by ftp (anonymous): ftp pianeta.di.unito.it cd pub/MLprog For questions or comments, please mail to: attilio@di.unito.it or neri@di.unito.it Attilio Giordana ------------------------------ From: Peter Clark Date: Thu, 23 Feb 1995 13:41:45 -0600 Subject: MACHINE LEARNING SOFTWARE AVAILABLE **************************************** MACHINE LEARNING SOFTWARE AVAILABLE **************************************** The following papers and software are now available from the WWW at: http://www.cs.utexas.edu/users/pclark/softare.html 1. Guiding Inductive Learning with a Qualitative Model This software is (an updated version) of that described in the paper "Using Qualitative Models to Guide Inductive Learning", by Peter Clark and Stan Matwin, pp49-56, Proc. Tenth International Machine Learning Conference (1993). Fed up with your induction algorithm producing stupid or incomprehensible rules? Look no further! INPUT: - A set of training examples - A qualitative model OUTPUT: - A set of propositional if...then... classification rules which are also "explainable" by the qualitative model This package allows a qualitative model to bias induction of propositional if...then... rules (using CN2), so that only rules which are also "explainable" by the qualitative model (approximately: having a corresponding path in the qualitative model) are found. The output of the algorithm is thus not just a set of classification rules, but also an explanation of *why* they are plausible, based on the qualitative background knowledge. This learning system thus filters out those rules which are nonsensical (with respect to the given background knowledge), thus integrating background knowledge into the learning process. AUTHORS: Peter Clark (pclark@cs.utexas.edu) & Stan Matwin (stan@csi.uottawa.ca) SOFTWARE: Implemented in Quintus Prolog. s/w includes Sparc executables, which can be run without needing Quintus Prolog or knowledge of Prolog. s/w includes source, documentation and the examples from the paper. 2. LPE - Lazy Partial Evaluation This software is described in the paper "Lazy Partial Evaluation: An Integration of Explanation-based Generalisation and Partial Evaluation", by Peter Clark and Rob Holte, pp 82-91, Proc. Ninth International Machine Learning Conference (1992). Lazy partial evaluation is a form of speed-up learning, when reasoning with a domain theory. It is a hybrid between: - partial evaluation (PE), where a procedure is "unwound" in all possible ways and the results cached and indexed. - explanation-based learning (EBL), where just execution paths through the procedure which prove specific theorems are identified and cached. LPE does "partial evaluation on demand". It can be advantageous over PE as it avoids redundant expansion of a procedure (hence saving memory and CPU time). It can be advantageous over EBL as it avoids proving theorems from scratch with the (slow) original domain theory (when no cached solution applies), and avoids the "masking effect" where suboptimal, cached solutions are chosen in preference to better solutions implicit in the domain theory (when a cached solution applies). AUTHORS: Peter Clark (pclark@cs.utexas.edu) & Rob Holte (holte@csi.uottawa.ca) SOFTWARE: Implemented in Quintus Prolog, it includes source, documentation and the examples from the paper. 3. CN2 Also available at this WWW site: Details about the 1991 implementation of CN2, described in "Rule induction with CN2: Some recent improvements", by Peter Clark and Robin Boswell, pp151-163, Proc. Fifth European Machine Learning Conference (EWSL-91) (1991). Peter Clark pclark@cs.utexas.edu http://www.cs.utexas.edu/users/pclark 23rd Feb 1995 ------------------------------ Date: Tue, 28 Feb 95 20:18:56 -0600 From: Grace Wahba Subject: `soft' classification Announcing: Smoothing Spline ANOVA for Exponential Families, with Application to the Wisconsin Epidemiological Study of Retinopathy. by Grace Wahba, Yuedong Wang, Chong Gu, Ronald Klein, MD and Barbara Klein, MD. UWisconsin- Madison Statistics Dept TR 940, Dec. 1994 (WWGKK) ftp: ftp.stat.wisc.edu/pub/wahba/exptl.ssanova.ps.gz Mosaic: http://www.stat.wisc.edu/~wahba/wahba.html - then click on ftp ....... GRKPACK: Fitting Smoothing Spline ANOVA Models for Exponential Families. by Yuedong Wang. UWisconsin- Madison Statistics Dept TR 942, Jan. 1995. (GRKPACK-doc) ftp: ftp.stat.wisc.edu/pub/wahba/grkpack.ps.gz Mosaic: http://www.stat.wisc.edu/~wahba/wahba.html - then click on ftp ........ In WWGKK we develop Smoothing Spline ANOVA (SS-ANOVA) models for estimating the probability that an instance (subject) will be in class 1 as opposed to class 0, given a vector of predictor variables t (`soft' classification). We observe {y_i, t(i), i = 1,..,n} where y_i is 1 or 0 according as subject i's response is `success' or `failure', and t(i) is a vector of predictor variables for the i-th subject. Letting p(t) be the probability that a subject whose predictor variables are t, has a `success' response, we estimate p(t) = exp{f(t)}/(1 + exp{f(t)}} from this data using a smoothing spline ANOVA representation of f. An ANOVA representation gives f as a sum of functions of one variable (main effects) plus sums of functions of two variables (two -factor interactions) ...etc. This representation provides an interpretable alternative to a neural net. The following issues are addressed in this paper; (1) Methods for deciding which terms in the ANOVA decomposition to include (model selection), (2) Methods for choosing good values of the regularization (smoothing) parameters, which control the bias-variance tradeoff, (3) Methods for making confidence statements concerning the estimate, (4) Numerical algorithms for the calculations, and, finally, (5) Public software (GRKPACK). The overall scheme is applied to data from the Wisconsin Epidemiologic Study of Diabetic Retinopathy (WESDR) to model the risk of progression of diabetic retinopathy {`success'} as a function of glycosylated hemoglobin, duration of diabetes and body mass index {t}. Cross sectional plots provide interpretable information about these risk factors. This paper provided the basis for Grace Wahba's Neyman Lecture. A preliminary version appeared in NIPS-6. GRKPACK-doc provides documentation for the code GRKPACK, which implements (2)-(4) above. The code for GRKPACK is available in netlib in the file gcv/grkpack.shar. It is recommended that it be retrieved via Mosaic: http://www.netlib.org goto The Netlib Repository, goto gcv, rather than via the robot mailserver, which may subdivide the file. Included in GRKPACK are several examples including the analysis described in WWGKK and the WESDR data. Comments and suggestions concerning the code are requested to be sent to Yuedong Wang yuedong@umich.edu. ------------------------------ From: aha@aic.nrl.navy.mil Subject: Special AI Review journal issue on Lazy Learning Date: Wed, 15 Feb 1995 15:40:04 -0500 (EST) Reminder: March 15, 1995 is the submission deadline for the special AI Review journal issue on "Lazy Learning" (i.e., instance-based, exemplar-based, case-based, memory-based, edited k-NN, etc.). For more information, please contact me at aha@aic.nrl.navy.mil or read the pages at http://www.aic.nrl.navy.mil/~aha/ai-review/home.html. Thanks, David Aha ------------------------------ From: Tom Bylander Subject: Question on t test Date: Wed, 15 Feb 1995 16:58:07 -0600 (CST) Suppose I compare the performance of two learning algorithms on a dataset by repeatedly dividing the dataset into training and test examples, and performing a paired-difference t test on the difference in test accuracy. There seems to be some controversy over this methodology because any two trials will not be, in some sense, independent. Some of the test examples in one trial will be training examples in the other trial, and vice versa. However, what is the difficulty in viewing the experiment in the following way? I assume a uniform probability distribution over a sample space that consists of the possible ways that the dataset can be divided up into training and test examples. Now if I take a random sample from this sample space, then the t test will be very appropriate assuming that the random variable being tested is not too far from normal. That is, one of the ground rules for the t test is that each element in the sample is independently drawn from the same probability distribution. Whether the elements are close or far apart by some measure is not a concern. I would like to know what, if anything, is wrong with this argument. Tom Bylander bylander@ringer.cs.utsa.edu ------------------------------ From: Cullen Schaffer Date: Fri, 17 Feb 95 17:08:17 EST Subject: conservation of generalization In my talk on conservation of generalization at MLC last summer, I mentioned that there is a "realistic" concept for which C4.5 performs better when its information-gain-based splitting criterion is replaced with an analogous information-loss-based criterion and challenged members of the community to guess it. The answer is included in a new paper available through our WWW server: http://louis.hunter.cuny.edu/hunter.dcs.home.html The title of the paper is Conservation of Generalization: A Case Study. Anyone desperate to get right to the answer can skip ahead to Section 4.6. Cullen ------------------------------ From: Arun Sharma Date: Tue, 21 Feb 1995 11:40:39 +1100 (EST) Subject: Announcement of a Post-Doctoral Position RESEARCH ASSOCIATE (Fixed Term) SCHOOL OF COMPUTER SCIENCE AND ENGINEERING University of New South Wales, Sydney, Australia REF. 131 Salary: A$36,345 -- A$40,087 per annum (A$1 = US$0.75 approx). The School of Computer Science and Engineering is seeking to employ a Research Associate for a project funded by the Australian Research Council. This project, based at School's Artificial Intelligence Laboratory, involves the development and evaluation of knowledge discovery tools (based on inductive logic programming) for databases. Duties will involve all aspects of the project: design and analysis of knowledge discovery tools, planning and running experiments, analysing results, assisting in the preparation of papers, and taking part in discussions and seminars. Applicants must have recently completed a PhD in Computer Science (preferably with specialization and publications in Machine Learning), and will be required to have excellent C and Prolog programming skills. Good communication skills, both written and oral and a knowledge and understanding of EEO/AA principles are required. Familiarity with concepts and techniques of Logic Programming and Deductive Databases is desirable. The appointment is initially for a period of 12 months with further renewal up to three years, dependent on funding. Enquiries may be directed to Dr Arun Sharma on telephone +61-2-385-3938, email: arun@cse.unsw.edu.au; Assoc Prof Claude Sammut on telephone +61-2-385-3933, email: claude@cse.unsw.edu.au; or Dr John Shepherd on telephone +61-2-385-3969, email: jas@cse.unsw.edu.au. Applications close 8 March 1995. Applications, mentioning the Reference number, should be sent to the following: The Recruitment Officer Human Resources Department The University of New South Wales Sydney, NSW 2052, Australia Fax: +61-2-662 2832 ------------------------------ Subject: NEW BOOK by Kluwer: Concept Formation and Knowledge Revision Date: Tue, 14 Feb 95 17:40:39 +0100 From: Stefan.Wrobel@gmd.de NEW BOOK by Kluwer Academic Publishers Concept Formation and Knowledge Revision Stefan Wrobel, GMD [See http://nathan.gmd.de/persons/stefan.wrobel/kluwerbook.html] Regarding concepts as the elementary representational vocabulary of an intelligent system, this book focuses on representation change as a concept formation task. Taking an interdisciplinary approach from psychological foundations to computer implementations, Concept Formation and Knowledge Revision draws on existing psychological results about the nature of human concepts and concept formation. The book shows that computational concept formation can usefully be understood as a demand-driven process triggered by the representational needs of the learning system, and that knowledge revision is a suitable context for such a process. In using a first-order representation, this book is part of the rapidly developing field of Inductive Logic Programming (ILP). It presents a detailed analysis of the revision problem for first-order clausal theories, describes suitable knowledge revision and concept formation operators, and demonstrates their usefulness both theoretically and empirically within the learning knowledge acquisition system MOBAL. By integrating computational issues with psychological and fundamental discussions of concept formation phenomena, the book will be of interest to a wide spectrum of readers, whether theoretically, cognitively or practically inclined. >From the foreword by Katharina Morik: "Machine learning - as artificial intelligence in general - grows from three different roots: cognition, theory, and applications. ... The ideal to combine the three sources of artificial intelligence research has almost never been reached. ... The most important capability for artificial intelligence is to keep the integrative view and to create a true original work that goes beyond the collection of pieces from different fields. In presenting the long way from psychological investigations to an implemented system and its theoretical foundation, this book achieves such an integrative view of concept formation and knowledge revision." Contents: Foreword. 1. Introduction. 2. The Psychology of Concepts and Concept Formation. 3. Concept Representation in a Paraconsistent Logic with Higher- Order Elements. 4. Knowledge Revision as a Concept Formation Context. 5. Demand-Driven Concept Formation. 6. Embeddedness. 7. Conclusion. A. MOBAL Software Info Page. B. Glossary of Symbols. Kluwer Academic Publishers, Dordrecht, Boston, London. 256 pp. Hardbound ISBN: 0-7923-9500-X. Prices: NLG: 160.00, USD: 79.95, GBP: 57.75. Limited number of discounted copies available directly from the author at DEM 59.95 (inside Germany), DEM 89.95/USD 59.95 (elsewhere). For order forms and further information, check out http://nathan.gmd.de/persons/stefan.wrobel/kluwerbook.html on the WWW, or send E-Mail to wrobel@gmd.de. ------------------------------ Date: Sun, 19 Feb 1995 13:03:59 -0500 From: Rich Sutton Subject: RL papers available by ftp The following previously published papers related to reinforcement learning are available online for the first time: Sutton, R.S. (1988) "Learning to predict by the methods of temporal differences," Machine Learning, 3, 1988, No. 1, pp. 9--44. Sutton, R.S. (1990) "Integrated architectures for learning, planning, and reacting based on approximating dynamic programming," Proceedings of the Seventh International Conference on Machine Learning, pp. 216--224, Morgan Kaufmann. Sutton, R.S. (1991a) "Planning by incremental dynamic programming," Proceedings of the Eighth International Workshop on Machine Learning, pp. 353-357, Morgan Kaufmann. Sutton, R.S. (1991b) "Dyna, an integrated architecture for learning, planning and reacting," Working Notes of the 1991 AAAI Spring Symposium on Integrated Intelligent Architectures} and SIGART Bulletin 2, pp. 160-163. Sutton, R.S. (1992a) "Adapting Bias by Gradient Descent: An Incremental Version of Delta-Bar-Delta," Proceedings of the Tenth National Conference on Artificial Intelligence, pp. 171-176, MIT Press. Sutton, R.S., Whitehead, S.D. (1993) "Online learning with random representations." Proceedings of the Tenth Annual Conference on Machine Learning, pp. 314-321, Morgan Kaufmann. These papers can be obtained by ftp from the small archive at ftp.gte.com/reinforcement-learning. See the file CATALOG for filenames and abstracts. ------------------------------ Date: Tue, 28 Feb 1995 15:02:57 +0600 From: "Douglas H. Fisher" Subject: Vanderbilt ML WWW page A list of titles and some online documents relating to research on machine learning and computational learning theory at Vanderbilt University (Gautam Biswas, Doug Fisher, Vijay Raghavan and students) can be found at: http://www.vuse.vanderbilt.edu/~dfisher/ml.html One of the on-line technical reports covers some new results in clustering that may be of interest to some in machine learning and knowledge discovery. Your comments and literature pointers are welcome and at your discretion (and mine) may be linked in and inform subsequent revision. The title and abstract follow. Iterative Optimization and Simplification of Hierarchical Clusterings (Technical Report CS-95-01) http://www.vuse.vanderbilt.edu/~dfisher/tech-reports/tr-95-01.html Doug Fisher Department of Computer Science Box 1679, Station B Vanderbilt University Nashville, TN 37235 ABSTRACT: Clustering is often used for discovering structure in data. Clustering systems differ in the objective function used to evaluate clustering quality and the control strategy used to search the space of clusterings. Ideally, the search strategy should consistently construct clusterings of high quality, but be computationally inexpensive as well. In general, we cannot have it both ways, but we can partition the search so that a system inexpensively constructs a `tentative' clustering for initial examination, followed by iterative optimization, which continues to search in background for improved clusterings. Given this motivation, we evaluate an inexpensive `sorting' strategy coupled with several control strategies for iterative optimization, each of which repeatedly modifies an initial clustering in search of a better one. One of these optimization strategies, inspired by work on macro-operator learning, appears to be novel in the clustering literature. Once a clustering has been constructed it is judged by analysts -- often according to task-specific criteria. Several authors have abstracted these criteria and posited a generic performance task akin to pattern completion, where the error rate over completed patterns is used to `externally' judge clustering utility. Given this performance task we adapt resampling-based pruning strategies used by supervised learning systems to the task of simplifying hierarchical clusterings, thus promising to ease post-clustering analysis. Finally, we propose a number of objective functions, based on attribute-selection measures for decision-tree induction, that might perform well on the error rate and simplicity dimensions. Keywords: clustering, iterative optimization, cluster validation, resampling, pruning, objective functions. http://www.vuse.vanderbilt.edu/~dfisher/dfisher.html (615) 343-4111 ------------------------------ Date: Wed, 15 Feb 95 13:11:02 EST From: David Yarowsky Subject: CFP: ACL-95 WVLC3 - Supervised Training vs Self-organizing Methods Keywords: Corpora, Self-Organization, Statistical Models, Unsupervised Learning *** PRIMARY CALL FOR PAPERS **** ACL's SIGDAT and SIGNLL present the THIRD WORKSHOP ON VERY LARGE CORPORA WHEN: June 30, 1995 - immediately following ACL-95 (June 27-29) WHERE: MIT, Cambridge, Massachusetts, USA WORKSHOP DESCRIPTION: As in past years, the workshop will offer a general forum for new research in corpus-based and statistical natural language processing. Areas of interest include (but are not limited to): sense disambiguation, part-of-speech tagging, robust parsing, term and name identification, alignment of parallel text, machine translation, lexicography, spelling correction, morphological analysis and anaphora resolution. This year, the workshop will be organized around the theme of: Supervised Training vs. Self-organizing Methods For example, the process of assigning word-sense or part-of-speech labels to text corpora has often relied on large, hand-annotated training corpora. These are very labor intensive to produce, and are rarely available in languages other than English. Can Machine Learning help? How far can statistical, self-organizing and connectionist technology go towards automating the tagging process, improving the quality of existing taggers, and extending the range of languages with tagged corpora? The workshop also encourages presentations of new or improved unsupervised learning algorithms, discussions of the learning paradigms, how to reduce the effort in setting up supervised training, and other issues in ML, focusing on applications in natural language processing. The theme will provide an organizing structure to the workshop, and offer a framework for debate. However, we expect and will welcome a diverse set of submissions in all areas of statistical and corpus-based NLP. PROGRAM CHAIRS: Ken Church - AT&T Bell Laboratories David Yarowsky - University of Pennsylvania SPONSORS: LEXIS-NEXIS, Division of Reed and Elsevier, Plc. The Association for Computational Linguistics (ACL) SIGDAT (ACL's special interest group for linguistic data and corpus-based approaches to NLP) SIGNLL (ACL's special interest group for natural language learning) FORMAT FOR SUBMISSION: Authors should submit a full-length paper (3500-8000 words), either electronically or in hard copy. Electronic submissions should be mailed to "yarowsky@unagi.cis.upenn.edu", and must either be (a) plain ascii text, (b) a single postscript file, or (c) a single latex file following the ACL-95 stylesheet (no separate figures or .bib files). Hard copy submissions should be mailed to Ken Church (address below), and should include four (4) copies of the paper. REQUIREMENTS: Papers should describe original work. A paper accepted for presentation cannot be presented or have been presented at any other meeting. Papers submitted to other conferences will be considered, as long as this fact is clearly indicated in the submission. SCHEDULE: Submission Deadline: March 20, 1995 Notification Date: April 18, 1995 Camera ready copy due: May 11, 1995 CONTACT: Ken Church David Yarowsky Room 2B-421 Dept. of Computer and Info. Science AT&T Bell Laboratories University of Pennsylvania 600 Mountain Ave. 200 S. 33rd St. Murray Hill, NJ 07974 USA Philadelphia, PA 19104-6389 USA e-mail: kwc@research.att.com email: yarowsky@unagi.cis.upenn.edu ------------------------------ Date: Wed, 15 Feb 95 19:45:28 PST From: John Koza Subject: GP-96 Call For Papers FIRST CALL FOR PAPERS (Version 1.0) GP-96 - GENETIC PROGRAMMING 96 July 28 - 31 (Sunday - Wednesday), 1996 Fairchild Auditorium Stanford University Stanford, California This first genetic programming conference will bring together people from the academic world, industry, and government who are interested in genetic programming. The conference program will include contributed papers, tutorials, an invited speaker, and informal meetings. Topics of interest include, but are not limited to, - new applications of genetic programming - theory - extensions and variations of genetic programming - parallelization techniques - mental models, memory, and state - operator and representation issues - relations to biology and cognitive systems - implementation issues - war stories Proceedings will be published by The MIT Press. HONORARY CHAIR (AND INVITED SPEAKER) John Holland, University of Michigan GENERAL CHAIR John Koza, Stanford University PROGRAM COMMITTEE (In Formation): - Russell J. Abbott, California State University, Los Angeles and The Aerospace Corporation - David Andre, Stanford University - Peter J. Angeline, Loral Federal Systems - Wolfgang Banzhaf, University of Dortmund, Germany - Samy Bengio, Centre National d'Etudes des Telecommunications, France - Scott Brave, Stanford University - Walter Cedeno, Primavera Systems Inc. - Nichael Lynn Cramer, BBN System and Technologies - Patrik D'haeseleer, University of New Mexico - Bertrand Daniel Dunay, System Dynamics International - Frederic Gruau, Stanford University - Richard J. Hampo, Ford Motor Company - Simon Handley, Stanford University - Hitoshi Hemmi, ATR, Kyoto, Japan - Thomas Huang, University of Illinois - Hitoshi Iba, Electrotechnical Laboratory, Japan - Martin A. Keane, Econometrics Inc. - Mike Keith, Allen Bradely Controls - Kenneth Marko, Ford Motor Company - Kenneth E. Kinnear, Jr., Adaptive Computing Technology - W. B. Langdon, University College, London - Martin C. Martin, Carnegie Mellon University - Sidney R Maxwell III - David Montana, BBN System and Technologies - Dr. Heinz Muehlenbein, GMD Research Center, Germany - Peter Nordin, University of Dortmund, Germany - Howard Oakley, Institute of Naval Medicine, United Kingdom - Franz Oppacher, Carleton University, Ottawa - Una-May O`Reilly, Carleton University, Ottawa - Michael Papka, Argonne National Laboratory - Timothy Perkis - Justinian P. Rosca, University of Rochester - Conor Ryan, University College Cork, Ireland - Malcolm Shute, University of Brighton - Eric V. Siegel, Columbia University - Karl Sims - Andrew Singleton, Creation Mechanics - Lee Spector, Hampshire College - Walter Alden Tackett, Neuromedia - Astro Teller, Carnegie Mellon University - Patrick Tufts, Brandeis University - V. Rao Vemuri, University of Califonia at Davis - Darrell Whitley, Colorado State University - Alden H. Wright, University of Montana - Byoung-Tak Zhang, GMD, Germany EXECUTIVE COMMITTEE OF PROGRAM COMMITTEE (In Formation) SPECIAL PROGRAM CHAIRS The main focus of the conference (and about two-thirds of the papers) will be on genetic programming. In addition, papers describing recent developments in closely related areas of evolutionary computation (particularly those addressing issues common to various areas of evolutionary computation) will be reviewed by special program committees appointed and supervised by the following special program chairs. - GENETIC ALGORITHMS: David E. Goldberg, University of Illinois - CLASSIFIER SYSTEMS: Rick Riolo, University of Michigan - EVOLUTIONARY PROGRAMMING: David Fogel, University of California at San Diego - EVOLUTION STRATEGIES: PROPOSALS HEREBY SOLICITED TUTORIALS Tutorials will overview (1) genetic programming, (2) closely related areas of evolutionary computation, and (3) neural networks, machine learning, and introductory molecular biology. Most tutorials will be on Sunday, July 28, 1996 and specific times and dates will be announced later. - INTRODUCTION TO GENETIC PROGRAMMING: John Koza, Stanford University - MACHINE LANGUAGE GENETIC PROGRAMMING: Peter Nordin, University of Dortmund, Germany - GENETIC PROGRAMMING USING BINARY REPRESENTATION: Wolfgang Banzhaf, University of Dortmund, Germany - GENETIC ALGORITHMS: David E. Goldberg, University of Illinois - EVOLUTIONARY PROGRAMMING: David Fogel, University of California at San Diego - EVOLUTIONARY COMPUTATION FOR CONSTRAINT OPTIMIZATION: Zbigniew Michalewicz, University of North Carolina - CLASSIFIER SYSTEMS: Robert Elliott Smith, University of Alabama - MOLECULAR BIOLOGY FOR COMPUTER SCIENTISTS: Russell B. Altman, Stanford University -NEURAL NETWORKS David E. Rumelhart, Stanford University - MACHINE LEARNING: Pat Langley, Stanford University - OTHER GENETIC PROGRAMMING TUTORIALS: PROPOSALS HEREBY SOLICITED INFORMATION FOR SUBMITTING PAPERS: Wednesday, January 10, 1996 is the deadline for receipt at the address below of seven (7) copies of each submitted paper. Papers are to be in single-spaced, 12-point type on 8 1/2" x 11" or A4 paper (no e-mail or fax) with full 1" margins at top, bottom, left, and right. Two-sided printing is preferred. Papers are to contain ALL of the following 9 items within a maximum of 10 pages, in this order: (1) title of paper, (2) author name(s), (3) author physical address(es), (4) author e-mail address(es), (5) author phone number(s), (6) a 100-200 word abstract of the paper, (7) the paper's category (chosen from one of the following five alternatives: genetic programming, genetic algorithms, classifier systems, evolutionary programming, or evolution strategy), (8) the text of the paper (including all figures and tables), and (9) bibliography. All other elements of the paper (e.g., acknowledgements, appendices, if any) must come within the maximum of 10 pages. Review criteria will include significance of the work, novelty, sufficiency of information to permit replication (if applicable), clarity, and writing quality. The first-named author (or other designated author) will be notified of acceptance or rejection and reviewer comments by approximately Monday, February 26, 1996. Details of the style of the camera-ready paper will be announced later, but will resemble the SAB-94 and ALIFE-94 conferences recently published by the MIT Press. The deadline for the camera- ready, revised version of accepted papers will be announced later but will be approximately Wednesday, March 20, 1996. Proceedings will be published by The MIT Press and will be available at the conference. One of the authors will be expected to present each accepted paper at the conference. HOUSING: Stanford is about 40 miles south of San Francisco, about 25 miles south of the SF airport, and about 25 miles north of San Jose. There are numerous hotels of all types adjacent to, or near, the campus (many along El Camino Real Avenue in Palo Alto and nearby Mountain View). An optional housing and meals package will be available from the Conference Department at Stanford and will be announced later. FOR MORE INFORMATION: E-mail: GP96@Cs.Stanford.Edu GP-96 Conference c/o John Koza Computer Science Department Margaret Jacks Hall Stanford University Stanford, CA 94305-2140 USA ------------------------------ Date: Thu, 16 Feb 95 08:23:57 PST From: KDD-95 Account Subject: KDD95: Final Call for Papers A brief reminder that the deadline for KDD-95 submissions is FRIDAY MARCH 3RD: FINAL CALL FOR PAPERS FOR The First International Conference on Knowledge Discovery and Data Mining (KDD-95) Montreal, Canada, August 20-21, 1995 Sponsored by AAAI and in Cooperation with IJCAI, Inc. Co-located with IJCAI-95. URL: http://info.gte.com/~kdd/kdd95.html PAPER SUBMISSION INFORMATION: Please submit 5 *hardcopies* of a short paper (a maximum of 9 single-spaced pages not including cover page but including bibliography, 1 inch margins, and 12pt font) by March 3, 1995. A cover page must include author(s) full address, E-MAIL, a 200 word abstract, and up to 5 keywords. This cover page must accompany the paper. IN ADDITION, an ascii text version of the cover page MUST BE SENT BY E-MAIL to kdd95@aig.jpl.nasa.gov by March 3, 1995. Please mail the papers to : KDD-95 AAAI 445 Burgess Drive Menlo Park, CA 94025-3496 U.S.A. send e-mail queries regarding submissions logistics to: kdd@aaai.org ------------------------------ Subject: GA conference registration info Date: Thu, 16 Feb 95 13:32:53 -0600 From: Robert Elliott Smith 6TH INTERNATIONAL CONFERENCE ON GENETIC ALGORITHMS July 15-19, 1995 University of Pittsburgh Pittsburgh, Pennsylvania, USA CONFERENCE COMMITTEE Stephen F. Smith, Chair Carnegie Mellon University Peter J. Angeline, Finance Loral Federal Systems Larry J. Eshelman, Program Philips Laboratories Terry Fogarty, Tutorials University of the West of England, Bristol Alan C. Schultz, Workshops Naval Research Laboratory Alice E. Smith, Local Arrangements University of Pittsburgh Robert E. Smith, Publicity University of Alabama The 6th International Conference on Genetic Algorithms (ICGA-95) brings together an international community from academia, government, and industry interested in algorithms suggested by the evolutionary process of natural selection, and will include pre-conference tutorials, invited speakers, and workshops. Topics will include: genetic algorithms and classifier systems, evolution strategies, and other forms of evolutionary computation; machine learning and optimization using these methods, their relations to other learning paradigms (e.g., neural networks and simulated annealing), and mathematical descriptions of their behavior. The conference host for 1995 will be the University of Pittsburgh located in Pittsburgh, Pennsylvania. The conference will begin Saturday afternoon, July 15, for those who plan on attending the tutorials. A reception is planned for Saturday evening. The conference meeting will begin Sunday morning July 16 and end Wednesday afternoon, July 19. The complete conference program and schedule will be sent later to those who register. TUTORIALS ICGA-95 will begin with three parallel sessions of tutorials on Saturday. Conference attendees may attend up to three tutorials (one from each session) for a supplementary fee (see registration form). Tutorial Session I 11:00 a.m.-12:30 p.m. I.A Introduction to Genetic Algorithms Melanie Mitchell - A brief history of Evolutionary Computation. The appeal of evolution. Search spaces and fitness landscapes. Elements of Genetic Algorithms. A Simple GA. GAs versus traditional search methods. Overview of GA applications. Brief case studies of GAs applied to: the Prisoner's Dilemma, Sorting Networks, Neural Networks, and Cellular Automata. How and why do GAs work? I.B Application of Genetic Algorithms Lawrence Davis - There are hundreds of real-world applications of genetic algorithms, and a considerable body of engineering expertise has grown up as a result. This tutorial will describe many of those principles, and present case studies demonstrating their use. I.C Genetics-Based Machine Learning Robert Smith - This tutorial discusses rule-based, neural, and fuzzy techniques that utilize GAs for exploration in the context reinforcement learning control. A rule-based technique, the learning classifier system (LCS), is shown to be analogous to a neural network. The integration of fuzzy logic into the LCS is also discussed. Research issues related to GA-based learning are overviewed. The application potential for genetics-based machine learning is discussed. Tutorial Session II 1:30-3:00 p.m. II.A Basic Genetic Algorithm Theory Darrell Whitley - Hyperplane Partitions and the Schema Theorem. Binary and Nonbinary Representations; Gray coding, Static hyperplane averages, Dynamic hyperplane averages and Deception, the K-armed bandit analogy and Hyperplane ranking. II.B Basic Genetic Programming John Koza - Genetic Programming is an extension of the genetic algorithm in which populations of computer programs are evolved to solve problems. The tutorial explains how crossover is done on program trees and illustrates how the user goes about applying genetic programming to various problems of different types from different fields. Multi-part programs and automatically defined functions are briefly introduced. II.C Evolutionary Programming David Fogel - Evolutionary programming, which originated in the early 1960s, has recently been successfully applied to difficult, diverse real-world problems. This tutorial will provide information on the history, theory, and practice of evolutionary programming. Case-studies and comparisons will be presented. Tutorial Session III 3:30-5:00 p.m. III.A Advanced Genetic Algorithm Theory Darrell Whitley - Exact Non-Markov models of simple genetic algorithms. Markov models of simple genetic algorithms. The Schema Theorem and Price's Theorem. Convergence Proofs, Exact Non-Markov models for permutation based representations. III.B Advanced Genetic Programming John Koza - The emphasis is on evolving multi-part programs containing reusable automatically defined functions in order to exploit the regularities of problem environments. ADFs may improve performance, improve parsimony, and provide scalability. Recursive ADFs, iteration-performing branches, various types of memories (including indexed memory and mental models), architecturally diverse populations, and point typing are explained. III.C Evolution Strategies Hans-Paul Schwefel and Thomas Baeck - Evolution Strategies in the context of their historical origin for optimization in Berlin in the 1960s. Comparison of the computer-versions (1+1) and (10,100) ES with classical optimum seeking methods for parameter optimization. Formal descriptions of ES. Global convergence conditions. Time efficiency in some simple situations. The role of recombination. Auto-adaptation of internal models of the environment. Multi-criteria optimization. Parallel versions. Short list of application examples. GETTING TO PITTSBURGH The Pittsburgh International Airport is served by most of the major airlines. Information on transportation from the airport and directions to the University of Pittsburgh campus, will be sent along with your conference registration confirmation letter. LODGING University Holiday Inn, 100 Lytton Avenue two blocks from convention site $92/day (single) $9 /day parking charge pool (indoor), exercise facilities Reserve by June 18. Call 412-682-6200. Hampton Inn, 3315 Hamlet Street 12 blocks from convention site $72/day (single) free parking, breakfast, and one-way airport transportation Reserve by July 1. Call 412-681-1000. Howard Johnson's, 3401 Boulevard of the Allies 12 blocks from convention site $56/day (single) free parking and Oakland transportation pool (outdoor) Reserve by June 13. Call 412-683-6100. Sutherland Hall (dorm), University Drive-Pitt campus 10 blocks from convention site (steep hill) $30/day, single no amenities (phone, TV, etc.) shared bathroom Reserve by July 1. Call 412-648-1100. CONFERENCE FEES REGISTRATION FEE Registrations received by June 11 are $250 for participants and $100 for students. Registrations received on or after June 12 and walk-in registrations at the conference will be $295 for participants and $125 for students. Included in the registration fee are entry to all technical sessions, several lunches, coffee breaks, reception Saturday evening, conference materials, and conference proceedings. TUTORIALS There is a separate fee for the Saturday tutorial sessions. Attendees may register for up to three tutorials (one from each tutorial session). The fee for one tutorial is $40 for participants and $15 for students; two tutorials, $75 for participants and $25 for students; three tutorials, $110 for participants and $35 for students. The deadline to register without a late fee is June 11. After this date, participants and students will be assessed a flat $20 late fee, whether they register for one, two, or all three tutorials. CONFERENCE BANQUET Not included in the registration fee is the ticket for the banquet. Participants may purchase banquet tickets for an additional $30. Note - Please purchase your banquet tickets nowQyou will be unable to buy them upon arrival. GUEST TICKETS Guest tickets for the Saturday evening reception are $10 each; guest tickets for the conference banquet are $30 each for adults and $10 each for children. Note - Please purchase additional tickets now - you will be unable to buy them upon arrival. CANCELLATION/REFUND POLICY For cancellations received up to and including June 1, a full refund will be given minus a $25 handling fee. FINANCIAL ASSISTANCE FOR STUDENTS With support from the Naval Center for Applied Research in Artificial Intelligence, Naval Research Laboratory, a limited fund has been set aside to assist students with travel expenses. Students should have their advisor certify their student status and that sufficient funds are not available. Students interested in obtaining such assistance should send a letter before May 22 describing their situation and needs to: Peter J. Angeline, c/o Advanced Technologies Dept, Loral Federal Systems, State Route 17C, Mail Drop 0210, Owego, NY 13827-3994 USA. TO REGISTER Early registration is recommended. You may register by mail, fax, or email using a credit card (MasterCard or VISA). You may also pay by check if registering by mail. Note: Students must also send with their registration a photocopy of their valid university student ID or a letter from a professor. Complete the registration form and return with payment. If more than one registrant from the same institution will be attending, make additional copies of the registration form. Mail ICGA 95 Department of Industrial Engineering University of Pittsburgh 1048 Benedum Hall Pittsburgh, PA 15261 USA Fax Fax the registration form to 412-624-9831 Email Receive email form by contacting: icga@engrng.pitt.edu Up-to-date conference information is available on the World Wide Web (WWW) http://www.aic.nrl.navy.mil/galist/icga95/ CALL FOR ICGA '95 WORKSHOP PROPOSALS ICGA workshop proposals are now being solicited. Workshops tend to range from informal sessions to more formal sessions with presentations and working notes. Each accepted workshop will be supplied with space and an overhead projector. VCRs might be available. If you are interested in organizing a workshop, send a workshop title, short description, proposed format, and name of the organizers to the workshop coordinator by April 15, 1995. Alan C. Schultz - schultz@aic.nrl.navy.mil Code 5510, Navy Center for Artificial Intelligence Naval Research Laboratory Washington DC 30375-5337 USA REGISTRATION FORM Prof / Dr / Mr / Ms / Mrs Name ______________________________________________________ Last First MI I would like my name tag to read _____________________________________________ Affiliation/Business ______________________________________________________ Address ______________________________________________________ City ______________________________________________________ State ___________________ Zip ________________________ Country_____________________________________________ Telephone (include area code) Business _______________________________ Home______________________________ FEES (all figures in US dollars) Conference Registration Fee By June 11 ___ participant, $250 ___ student, $100 =$_________ On or after June 12 ___ participant, $295 ___ student, $125 =$_________ July 15 Tutorials Select up to three tutorials, but no more than one tutorial per tutorial session. Tutorial Session I: ___I.A Introduction to Genetic Algorithms ___I.B Application of Genetic Algorithms ___I.C Genetics-Based Machine Learning Tutorial Session II: ___II.A Basic Genetic Algorithm Theory ___II.B Basic Genetic Programming ___II.C Evolutionary Programming Tutorial Session III: ___III.A Advanced Genetic Algorithm Theory ___III.B Advanced Genetic Programming ___III.C Evolution Strategies Tutorial Registration Fee By June 11 ___one tutorial: participant, $40 student, $15 ___two tutorials: participant, $75 student, $25 = $_________ ___three tutorials: participant, $110 student, $35 On or after June 12, participants and students add a $20 late fee for tutorials = $_________ Banquet Ticket (not included in the Registration Fee; no tickets may be purchased upon arrival) participants/adult guest #______ ticket(s) @ $30 = $_________ child #______ ticket(s) @ $10 = $_________ Additional Saturday reception tickets (no tickets may be purchased upon arrival) guest #______ ticket(s) @ $10 = $_________ TOTAL (US dollars) $____________ METHOD OF PAYMENT ___ Check (payable to the University of Pittsburgh, US banks only) ___ MasterCard ___ VISA #__________________________________________ Expiration Date ____________________ Signature of card holder ______________________________________________ Note: Students must submit with their registration a photocopy of their valid student ID or a letter from a professor. Mail ICGA 95, Department of Industrial Engineering, University of Pittsburgh, 1048 Benedum Hall, Pittsburgh, PA 15261 USA Fax 412-624-9831 Email To receive email form: icga@engrng.pitt.edu World Wide Web (WWW) For up-to-date conference information: http://www.aic.nrl.navy.mil/galist/icga95/ ------------------------------ Subject: CFP-ML95-PbD Workshop Date: Mon, 20 Feb 1995 16:30:24 +0100 From: Holger &h -4243 Announcement & Call for Papers Learning from Examples vs. Programming by Demonstration: Is interaction the key to (better) applications? Workshop at ICML'95, Tahoe City, California, USA, July 9th, 1995 Background: Inductive Learning from Examples (LfE) is a well established subject in Machine Learning. "Pure" LfE is performed automatically without any human interaction. Programming by Demonstration (PbD) on the other hand can be seen as some kind of "extreme" form of user-supported LfE where the user continually interacts with a PbD system. The nearly exclusive focus of it is the learning of programs. PbD researchers have been disappointed with standard ML algorithms. They require too many examples or too strong a domain theory. Moreover they do not learn "useful" concepts that deterministically generate or modify data, but rather learn how to classify. Finally they easily get out of the user's control. Therefore, PbD applications to date have relied on pragmatic assumptions, application-specific heuristics, and manual intervention, to make plausible inferences from very few examples. Although this approach has yielded some successful early results, the systems require considerable engineering and have strict and often counter-intuitive limits on their adaptability. ML techniques integrated with user interaction hold out the promise of simpler, more capable systems. But the dialog between ML and PBD is just beginning. Scope: The workshop aims at bringing together researchers from the Machine Learning as well as different application areas. These include robotics, graphics interface development, office automation, and interactive software design. Topics of interest include, but are not limited to: - Combining LfE with user interaction to create working PbD applications - Acquisition and maintainance of control-knowledge using interaction - Relations between an agent's background knowledge, reasoning methods, and user interaction abilities - Which results of LfE are not used in PbD systems today, and why? - Effects of PbD system development on existing ML techniques and problems - User interfaces and system architectures for PbD systems - Why does PbD receive only little attention in the ML community so far? Submission of Papers: Paper submissions are limited to 5000 words. The title page must contain the title of the talk, name(s) and affiliation(s) of the author(s) and a list of keywords as well as the full address (including E-Mail) of the first author. A sample paper, a LaTeX- style file and a MS-Word file are available via ftp from 'ftpipr.ira.uka.de' in the directory 'pub/conferences/ML95-PBD'. A laser-quality copy of the paper must be received by the workshop organizers by April 7th, 1995. The electronic submission of papers in Postscript format to 'ftpipr.ira.uka.de' is encouraged. Accepted papers (about 9) will be published in the Workshop notes, the best papers will be selected for a special issue of AI and Engineering Applications. Important Dates: Submission deadline: April 7th, 1995 Notification of acceptance: May 2nd, 1995 Camera-ready paper: June 9th, 1995 Workshop: July 9th, 1995 Program Committee: S. Bocionek (Munich, Germany) R. Dillmann (Karlsruhe, Germany) A. Giordana (Turin, Italy) Y. Kuniyoshi (Tsukuba, Japan) D. Maulsby (Cambridge, USA) Workshop information and submission of papers to: Holger Friedrich University of Karlsruhe Institute for Real-Time Computer Systems & Robotics D-76128 Karlsruhe, Germany E-Mail: friedric@ira.uka.de ftp: ftpipr.ira.uka.de Workshop site information: Publicity Chair of ML'95: Jeff Schlimmer Washington State University, USA E-Mail: schlimme@eecs.wsu.edu Local Arrangments for ML'95: Debbie Chadwick UC at Davis, USA E-Mail: chadwick@cs.ucdavis.edu General Inquiries about ML'95: E-Mail: ml95@cs.ucdavis.edu WWW: http://www.eecs.wsu.edu/~schlimme/ml95.html >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>><<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<< >> This Call for Papers is also available as 300dpi Postscript File << >> at the anonymous ftp server ftpipr.ira.uka.de in the directory << >> 'pub/conferences/ML95-PBD'. << >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>><<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<< ------------------------------ Date: Tue, 21 Feb 1995 10:36:44 +0001 From: NADA LAVRAC Subject: Welcome to ECML-95 ******************************************************* * Welcome to ECML-95 * ******************************************************* ECML-95 The 8th EUROPEAN CONFERENCE ON MACHINE LEARNING 25--27 April 1995, Heraklion, Crete, Greece URL ftp://ftp.gmd.de/ml-archive/general/ecml-95/ecml95.html Welcome to ECML-95 ! Continuing the tradition of previous EWSL and ECML conferences, ECML-95 provides the major European forum for presenting the advances in the area of Machine Learning. Invited talks: ************** Rudolf Kruse Reasoning and Learning in Probabilistic and Possibilistic Networks (proceedings paper by J. Gebhardt and R. Kruse) Donald Michie Problem Decomposition and the Learning of Skills (proceedings paper by D. Michie) Tom Mitchell Machine Learning in the World Wide Web Stellan Ohlsson Abstract Computer Models: Towards a New Method for Theorizing about Adaptive Agents (proceedings paper by S. Ohlsson and J.J. Jewett) The list of accepted papers and posters (including all abstracts) is available from the ECML-95 WWW home page ftp://ftp.gmd.de/ml-archive/general/ecml-95/ecml95.html This page also gives access to ECML-95 registration information. For further questions about the program, contact the program chairs (N. Lavrac & S. Wrobel) at ecml-95@gmd.de. For information about MLNet familiarization workshops following ECML-95, contact Derek Sleeman (E-mail: mlnet@computing-science.aberdeen.ac.uk). For questions about registration, contact the local chair V. Moustakis at ecml-95@ics.forth.gr. ------------------------------ Date: Thu, 16 Feb 1995 15:42:24 +0200 From: Account for mlt meeting Subject: ECML-95 ECML - 95 8th European Conference on Machine Learning 25-27 April 1995, Heraklion, Crete, Greece MLnet FWS - 95 MLnet 3rd Familiarization Workshop Series 28-29 April 1995, Heraklion, Crete, Greece REGISTRATION FORM ___________________ Please make certain that this form is received by the 17th of February 1995 along with payment by (please use FAX or regular mail): Ms. Maria Prevelianaki ECML-95 Secretary Institute of Computer Science (ICS) Foundation for Research and Technology (FORTH) P.O Box 1385 711 10 Heraklion, Crete, Greece Tel.: +30-81-391604, 391600 Fax : +30-81-391601 E-mail: ecml-95@ics.forth.gr NAME: ___________________________________________________________________ AFFILIATION: ____________________________________________________________ FULL ADRESS: ____________________________________________________________ _________________________________________________________________________ _________________________________________________________________________ TEL:_____________________________________________________________________ FAX:_____________________________________________________________________ E_MAIL:__________________________________________________________________ Registration fee: 50000 drs. before February 24, 1995 (ECML 95) 58000 drs. before April 7, 1995 69000 drs. after April 7, 1995 Fee: ________ drs. Registration fee: 21000 drs. before February 17, 1995 (MLnet FWS 95) 25000 drs. after April 7, 1995 Fee(*): ______ drs. (*) If you have been awarded an MLnet bursary for MLnet FWS-95 please indicate your bursary reference number: __________ To obtain an MLnet bursary application form please contact: Davide Roverso (MLnet Admin.) Tel: +44-1224-272304 Dept. of Computing Science Fax: +44-1224-273422 University of Aberdeen E_mail: mlnet@csd.abdn.ac.uk ABERDEEN, AB9 2UE Scotland, UK Note that MLnet bursary are normally reserved to members of MLnet nodes. Hotel Information: We have secured a limited number of rooms in various hotels inside Heraklion: HOTEL CLASS SINGLE DOUBLE GALAXY A Lux 19200 20500 GALAXY A 15300 16500 ASTORIA A 15300 16500 LATO C 9600 12800 EL_GRECO C 9000 11700 Please indicate your preference: 1st preference : _________________________(single/double) 2nd preference : _________________________(single/double) 3rd preference : _________________________(single/double) Specify with whom you wish to share the room: _________________________ (if applicable) Please include the amount that corresponds to the most expensive preference. Excess funds will be credited to your amount. Hotel reservation cannot be refunded. ECML-95 Registration fee: _________________________ drs. One night accommodation advance payment: _________________________drs. MLnet FWS Registration fee: _________________________ drs. Arrival:______________________ April 1995 Flight: ___________________ Departure: ___________________ April 1995 Flight: ___________________ Total number of nights for which you need a reservation:___________________ Conference Dinner: 8000 drs. (optional) ___________________ Additional person fee : 12000 drs. (includes reception and Conference Dinner, optional) ___________________ TOTAL AMOUNT: ___________________ Method of payment: * Swift funds to ERGOGRAA, ERGOBANK S.A, Heraklion, Crete, Greece, to ECML-95 account. * Or send a bank cheque payable to ECML-95 and drawn on ERGOBANK S.A. Cheques should be sent to Maria Prevelianaki. * Personal cheques will not be accepted. * If you use a credit card please sign the attached authorization form: Credit card (VISA/MASTERCARD/AMERICAN EXPRESS). Please fill in: I authorize to charge my card the amount of ___________________ drs. Name:__________________________________________________________ Card number: ___________________ Exp. date:___________________ Signature: _____________________ Date: _______________________ Cancellation Policy: Hotel deposit generally cannot be refunded. Registration fee, accompanying person and dinner participation will be refunded minus Bank and related processing expenses. Travel Agency: KATREA Travel (Mr. George Alexakis) handles the administration of hotels and other Conference matters. Participants may wish too contact KATREA for further tourist information. Adress: Pediados 3, P.O Box 1353, 712 01 Heraklion, Greece. Tel: +30-81-281749, 391918-9 Fax: +30-81-281779 MLNet FWS Workshops : A) Knowledge Level Modelling and Machine Learning Please contact: Dieter Fensel fiensel@swi.psy.uva.nl +31 20 525 6791 (voice) +31 20 525 6896 (fax) B) Learning Robots Please contact: Michael Kaiser kaiser@ira.uka.de +49 721 608 4051 (voice) +49 721 606 740 (fax) C) Statistics, Machine Learning, and Discovery in Data Bases Gholamreza Nakhaeizadeh nakhaeizadeh@dbag.ulm.DaimlerBenz.COM +49 731 505 2860 (voice) +49 731 505 4210 To participate in MLNet FWS you should get approval from the workshop organiser and also notify MLNet Office (Mr. Davide Roverso). I have submitted a paper to the A / B / C workshop (delete as appropriate) I would like to attend workshop A / B / C (delete as appropriate) ------------------------------ Date: Thu, 23 Feb 1995 13:41:37 -0500 From: Russell Greiner Subject: CFP: "Relevance" issue of "Artificial Intelligence" ************************************************************** ***** CALL FOR PAPERS (please post) ****** ************************************************************** Special Issue on RELEVANCE Journal: ARTIFICIAL INTELLIGENCE Guest Editors: Russell Greiner, Devika Subramanian, Judea Pearl With too little information, reasoning and learning systems cannot work effectively. Surprisingly, too much information can also cause the performance of these systems to degrade, in terms of both accuracy and efficiency. It is therefore important to determine what information must be preserved, i.e., what information is "relevant". There has been a recent flurry of interest in explicitly reasoning about relevance in a number of different disciplines, including the AI fields of knowledge representation, probabilistic reasoning, machine learning and neural computation, as well as communities that range from statistics and operations research to database and information retrieval to cognitive science. Members of these diverse communities met at the 1994 AAAI Fall Symposium on Relevance, to seek a better understanding of the various senses of the term "relevance", with a focus on finding techniques for improving the performance of embedded agents by ignoring or de-emphasizing irrelevant and superfluous information. Such techniques will clearly be of increasing importance as knowledge bases, and learning systems, become more comprehensive to accommodate real-world applications. To help consolidate leading research on relevance, the "Artificial Intelligence" journal is devoting a special issue to this topic. We are now seeking papers on (but not restricted to) the following topics: [Representing and reasoning with relevance:] reasoning about the relevance of distinctions to speed up computation, relevance reasoning in real-world KR tasks including design, diagnosis and common-sense reasoning, use of relevant causal information for planning, theories of discrete approximations. [Learning in the presence of irrelevant information:] removing irrelevant attributes and/or irrelevant training examples, to make feasible induction from very large datasets; methods for learning action policies for embedded agents in large state spaces by explicit construction of approximations and abstractions. [Relevance and probabilistic reasoning:] simplifying/approximating Bayesian nets (both topology and values) to permit real-time reasoning; axiomatic bases for constructing abstractions and approximations of Bayesian nets and other probabilistic reasoning models. [Relevance in neural computational models:] methods for evolving computations that ignore aspects of the environment to make certain classes of decisions, automated design of topologies of neural models guided by relevance reasoning based on task class. [Applications of relevance reasoning:] Applications that require explicit reasoning about relevance in the context of IVHS, exploring and understanding large information repositories, etc. We are especially interested in papers that have strong theoretical analyses complemented by experimental evidence from non-trivial applications. Authors are invited to submit manuscripts conforming to the AIJ submission requirements by 11 Sept 1995 to Russell Greiner or Devika Subramanian Siemens Corporate Research Department of Computer Science 755 College Road East 5141 Upson Hall, Cornell University Princeton, NJ 08540-6632 Ithaca, New York 14853 (609) 734-3627 (607) 255-9189 Papers will be a subject to a standard peer review. The first round of reviews will be completed and decisions mailed by 11 December 1995. The authors of accepted and conditionally accepted manuscripts will be required to send revised versions by 1 March 1996. The special issue is tentatively scheduled to appear sometime in 1996. We also plan to publish this issue as a book. Finally, to help us select appropriate reviewers in advance, authors should email us a title, set of keywords and a short abstract, to arrive by 4 September. To recap the significant dates: 4/Sep/95: Emailed titles, keywords and abstracts due 11/Sep/95: Manuscripts dues 11/Dec/95: First round decisions 1/Mar/96: revised manuscripts due ?? /96: special issue appears (tentative) ------------------------------ From: Office Account Date: Thu, 23 Feb 1995 14:53:33 -0700 Subject: MaxEnt95 ANNOUNCEMENT AND CALL FOR PAPERS The Fifteenth International Workshop on Maximum Entropy and Bayesian Methods 30 July - 4 August 1995 St. John's College Santa Fe, New Mexico, USA The Fifteenth International Workshop on Maximum Entropy and Bayesian Methods will be held at St. John's College in Santa Fe, New Mexico, USA. This Workshop is being jointly sponsored by the Center for Nonlinear Studies and the Radiographic Diagnostics Program, both at Los Alamos National Laboratory, and by the Santa Fe Institute (SFI). SCOPE: Traditional themes of the Workshop have been the application of the maximum entropy principle and Bayesian methods for statistical inference to diverse areas of scientific research. Practical numerical algorithms and principles for solving ill-posed inverse problems, image reconstruction and model building are emphasized. The Workshop also addresses common foundations for statistical physics, statistical inference, and information theory. The Workshop will begin on 31 July with a half-day tutorial on Bayesian methods and the principle of maximum entropy, which will be presented by Wray Buntine and Peter Cheeseman of NASA. The Workshop will also include several reviews of hot topics of broad interest, such as Markov Chain Monte Carlo methods for sampling posteriors, deformable geometric models, and the relation between information theory and physics. Specially organized sessions will highlight other topics, such as Bayesian time-series analysis, entropies in dynamical systems, and data analysis for physics simulations. The Workshop will be held in the beautiful setting of St. John's College, nested in the foothills of the Sangre de Cristo Mountains, two miles from the Santa Fe Plaza. St. John's is a small liberal arts college, which emphasizes a classical curriculum. Social events include a reception at the Santa Fe Institute and an outing to the Science Museum at the Los Alamos National Laboratory. The timing of the Workshop coincides with the peak of the Santa Fe tourist and opera seasons. CALL FOR CONTRIBUTED PAPERS: Contributed papers are requested on the innovative use of Bayesian methods or the maximum entropy principle. The deadline for receipt of abstracts is April 14, 1995. They should be written in LaTeX or ascii and limited to one page of about 400 words. Please include a curriculum vita or a short biographical sketch. Specify preference for an oral or poster presentation. The abstracts will be made available at the Workshop. Manuscripts of accepted papers will be due at the Workshop, in camera-ready form, on diskette, and one hard-copy, and they must be prepared in LaTeX using a style file that will be made available to authors by e-mail or by post. REGISTRATION: To receive registration materials and detailed information about this Workshop, contact Ms. Barbara Rhodes at the address below. Space limitations at St. John's College will restrict the number of attendees to about 125. Early registration will help to assure a place at the meeting. SCHOLARSHIPS: Limited financial support will be available to assist graduate students and postdoctoral fellows who wish to attend the workshop. Requests for support may be submitted along with registration materials. SCIENTIFIC ORGANIZERS: Kenneth Hanson and Richard Silver, Los Alamos National Laboratory Send abstracts and requests for registration materials and other information to the administrative organizer: Ms. Barbara Rhodes Tel: (505) 667-1444 CNLS, MS-B258 Fax: (505) 665-2659 Los Alamos National Laboratory E-mail: maxent@cnls.lanl.gov Los Alamos, NM 87545 USA ------------------------------ Date: Mon, 27 Feb 95 11:52:03 EST From: David Cohn Subject: NIPS*95 Call for Papers CALL FOR PAPERS Neural Information Processing Systems Natural and Synthetic Monday, Nov. 27 - Saturday, Dec. 2, 1995 Denver, Colorado This is the ninth meeting of an interdisciplinary conference which brings together neuroscientists, engineers, computer scientists, cognitive scientists, physicists, and mathematicians interested in all aspects of neural processing and computation. The confer- ence will include invited talks, and oral and poster presenta- tions of refereed papers. There will be no parallel sessions. There will also be one day of tutorial presentations (Nov. 27) preceding the regular session, and two days of focused workshops will follow at a nearby ski area (Dec. 1-2). Major categories for paper submission, with example subcategories, are as follows: Neuroscience: systems physiology, signal and noise analysis, oscillations, synchronization, mechanisms of inhibition and neuromodulation, synaptic plasticity, computational models Theory: computational learning theory, complexity theory, dynamical systems, statistical mechanics, probability and statistics, approximation and estimation theory Implementation: analog and digital VLSI, novel neuro-devices, neurocomputing systems, optical, simulation tools, parallelism Algorithms and Architectures: learning algorithms, decision trees constructive/pruning algorithms, localized basis func- tions, recurrent networks, genetic algorithms, combinatorial optimization, performance comparisons Visual Processing: image recognition, coding and classifica- tion, stereopsis, motion detection and tracking, visual psycho- physics Speech, Handwriting and Signal Processing: speech recognition, coding and synthesis, handwriting recognition, adaptive equali- zation, nonlinear noise removal, auditory scene analysis Applications: time-series prediction, medical diagnosis, finan- cial analysis, DNA/protein sequence analysis, music processing, expert systems, database mining Cognitive Science & AI: natural language, human learning and memory, perception and psychophysics, symbolic reasoning Control, Navigation, and Planning: robotic motor control, pro- cess control, navigation, path planning, exploration, dynamic programming, reinforcement learning Review Criteria: All submitted papers will be thoroughly refereed on the basis of technical quality, novelty, significance, and clarity. Submissions should contain new results that have not been published previously. Authors should not be dissuaded from submitting recent work, as there will be an opportunity after the meeting to revise accepted manuscripts before submitting final camera-ready copy. Paper Format: Submitted papers may be up to eight pages in length, including figures and references. The page limit will be strictly enforced, and any submission exceeding eight pages will not be considered. Authors are encouraged (but not required) to use the NIPS style files obtainable by anonymous FTP at the sites given below. Papers must include physical and e-mail addresses of all authors, and MUST indicate one of the nine major categories listed above. Authors may also indicate a subcategory, and their preference, if any, for oral or poster presentation; this preference will play no role in paper acceptance. Unless otherwise indicated, correspondence will be sent to the first au- thor. Submission Instructions: Send six copies of submitted papers to the address below; electronic or FAX submission is not accept- able. Include one additional copy of the abstract only, to be used for preparation of the abstracts booklet distributed at the meeting. Submissions mailed first-class from within the US or Canada, or sent from overseas via Federal Express/Airborne/DHL or similar carrier must be POSTMARKED by May 20, 1995. All other submissions must ARRIVE by this date. Mail submissions to: Michael Mozer NIPS*95 Program Chair Department of Computer Science University of Colorado Colorado Avenue and Regent Drive Boulder, CO 80309-0430 USA Mail general inquiries/requests for registration material to: NIPS*95 Registration Dept. of Mathematical and Computer Sciences Colorado School of Mines Golden, CO 80401 USA FAX: (303) 273-3875 e-mail: nips95@mines.colorado.edu Sites for LaTex style files: Copies of "nips.tex" and "nips.sty" are available via anonymous ftp at helper.systems.caltech.edu (131.215.68.12) in /pub/nips, b.gp.cs.cmu.edu (128.2.242.8) in /usr/dst/public/nips. The style files and other conference information may also be retrieved via World Wide Web at http://www.cs.cmu.edu:8001/Web/Groups/NIPS/NIPS.html NIPS*95 Organizing Committee: General Chair, David S. Touretzky, CMU; Program Chair, Michael Mozer, U. Colorado; Publications Chair, Michael Hasselmo, Harvard; Tutorial Chair, Jack Cowan, U. Chicago; Workshops Chair, Michael Perrone, IBM; Publicity Chair, David Cohn, MIT; Local Arrangements, Manavendra Misra, Colorado School of Mines; Treasurer, John Lazzaro, Berkeley. DEADLINE FOR SUBMISSIONS IS MAY 20, 1995 (POSTMARKED) -please post- ------------------------------ Date: Mon, 27 Feb 95 11:52:51 EST From: David Cohn Subject: NIPS*95 Call for Workshop Proposals CALL FOR PROPOSALS NIPS*95 Post Conference Workshops December 1 and 2, 1995 Vail, Colorado Following the regular program of the Neural Information Processing Systems 1995 conference, workshops on current topics in neural information processing will be held on December 1 and 2, 1995, in Vail, Colorado. Proposals by qualified individuals interested in chairing one of these workshops are solicited. Past topics have included: active learning and control, architectural issues, at- tention, bayesian analysis, benchmarking neural network applica- tions, computational complexity issues, computational neurosci- ence, fast training techniques, genetic algorithms, music, neural network dynamics, optimization, recurrent nets, rules and connec- tionist models, self-organization, sensory biophysics, speech, time series prediction, vision and audition, implementations, and grammars. The goal of the workshops is to provide an informal forum for researchers to discuss important issues of current interest. Sessions will meet in the morning and in the afternoon of both days, with free time in between for ongoing individual exchange or outdoor activities. Concrete open and/or controversial issues are encouraged and preferred as workshop topics. Representation of alternative viewpoints and panel-style discussions are partic- ularly encouraged. Individuals proposing to chair a workshop will have responsibilities including: 1) arranging short informal presentations by experts working on the topic, 2) moderating or leading the discussion and reporting its high points, findings, and conclusions to the group during evening plenary sessions (the "gong show"), and 3) writing a brief summary. Submission Instructions: Interested parties should submit a short proposal for a workshop of interest postmarked by May 20, 1995. (Express mail is not necessary. Submissions by electronic mail will also be accepted.) Proposals should include a title, a description of what the workshop is to address and accomplish, the proposed length of the workshop (one day or two days), and the planned format. It should motivate why the topic is of in- terest or controversial, why it should be discussed and what the targeted group of participants is. In addition, please send a brief resume of the prospective workshop chair, a list of publi- cations and evidence of scholarship in the field of interest. Submissions should include contact name, address, email address, phone number and fax number if available. Mail proposals to: Michael P. Perrone NIPS*95 Workshops Chair IBM T.J. Watson Research Center P.O. Box 704 Yorktown Heights, NY 10598 (email: mpp@watson.ibm.com) PROPOSALS MUST BE POSTMARKED BY MAY 20, 1995 -Please Post- ------------------------------ Date: Tue, 28 Feb 1995 10:17:10 +0500 From: Peter Turney Subject: Workshop on Data Engineering for Inductive Learning Workshop on Data Engineering for Inductive Learning Second and Final Call for Participation IJCAI-95, Montreal (Canada), August 20, 1995 This notice is to inform you that the date of the workshop has been determined and to remind you of the approaching deadline for submissions (including requests for participation without a paper presentation). In inductive learning, algorithms are applied to data. It is well-understood that attention to both elements is critical, but algorithms typically receive more attention than data. Our goal in this workshop is to counterbalance the predominant focus on algorithms by providing a forum in which data takes center stage. Specifically, we invite discussion of issues relevant to data engineering, which we define as the transformation of raw data into a form useful as input to algorithms for inductive learning. Data engineering is a concern in industrial and commercial applications of machine learning, neural networks, genetic algorithms, and traditional statistics. Deadline for submissions: March 31, 1995 Notification of acceptance: April 21, 1995 Submissions available by ftp: April 28, 1995 Actual Workshop: August 20, 1995 For more information about the workshop, see: http://ai.iit.nrc.ca/ijcai/data-engineering.html If you do not have access to the web, contact: peter@ai.iit.nrc.ca ------------------------------ End of ML-LIST (Digest format) **************************************** From cns-cas@PARK.BU.EDU Wed Mar 1 15:06:18 1995 Received: from cs.wisc.edu by sea.cs.wisc.edu; Wed, 1 Mar 95 15:06:09 -0600; AA11231 Received: from TELNET-1.SRV.CS.CMU.EDU by cs.wisc.edu; Wed, 1 Mar 95 15:06:05 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa01665; 1 Mar 95 14:22:02 EST Received: from GS151.SP.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa01663; 1 Mar 95 14:06:55 EST Received: from GS151.SP.CS.CMU.EDU by GS151.SP.CS.CMU.EDU id aa26645; 1 Mar 95 14:06:18 EST Received: from MAILBOX.SRV.CS.CMU.EDU by B.GP.CS.CMU.EDU id aa25174; 28 Feb 95 16:26:30 EST Received: from PARK.BU.EDU by MAILBOX.SRV.CS.CMU.EDU id aa08042; 28 Feb 95 16:25:44 EST Received: from sharp.bu.edu by cns.bu.edu (8.6.9/BU_Server-1.1) id QAA24008; Tue, 28 Feb 1995 16:13:42 -0500 Received: by sharp.bu.edu (8.6.9/BU_Client-1.1) id QAA07418; Tue, 28 Feb 1995 16:13:40 -0500 From: cns-cas@PARK.BU.EDU Mmdf-Warning: Parse error in original version of preceding line at MAILBOX.SRV.CS.CMU.EDU Message-Id: <199502282113.QAA07418@sharp.bu.edu> Subject: VISION, BRAIN, AND THE PHILOSOPHY OF COGNITION To: massmail@PARK.BU.EDU Date: Tue, 28 Feb 95 16:13:39 EST Cc: cindy@PARK.BU.EDU X-Mailer: ELM [version 2.3 PL11] VISION, BRAIN, AND THE PHILOSOPHY OF COGNITION Friday, March 17, 1995 Boston University George Sherman Union Conference Auditorium, Second Floor 775 Commonwealth Avenue Boston, MA 02215 Co-Sponsored by the Department of Cognitive and Neural Systems, the Center for Adaptive Systems, and the Center for Philosophy and History of Science Program: -------- 8:30am--9:30am: KEN NAKAYAMA, Harvard University, Visual perception of surfaces 9:30am--10:30am: RUDIGER VON DER HEYDT, Johns Hopkins University, How does the visual cortex represent surface and contour? 10:30am--11:00am: Coffee Break 11:00am--12:00pm: STEPHEN GROSSBERG, Boston University, Cortical dynamics of visual perception 12:00pm--1:00pm: PATRICK CAVANAGH, Harvard University, Attention-based visual processes 1:00pm--2:30pm: Lunch 2:30pm--3:30pm: V.S. RAMACHANDRAN, University of California, Neural plasticity in the adult human brain: New directions of research 3:30pm--4:30pm: EVAN THOMPSON, Boston University, Phenomenology and computational vision 4:30pm--5:30pm: DANIEL DENNETT, Tufts University, Filling-in revisited 5:30pm---: Discussion Registration: ------------- The conference is free and open to the public. Parking: -------- Parking is available at nearby campus lots: 808 Commonwealth Avenue ($6 per vehicle), 766 Commonwealth Avenue ($8 per vehicle), and 700 Commonwealth Avenue ($10 per vehicle). If these lots are full, please ask the lot attendant for an alternate location. Contact: -------- Professor Stephen Grossberg Department of Cognitive and Neural Systems 111 Cummington Street Boston, MA 02215 fax: (617) 353-7755 email: diana@cns.bu.edu From schlimme@eecs.wsu.edu Thu Mar 2 06:52:29 1995 Received: from cs.wisc.edu by sea.cs.wisc.edu; Thu, 2 Mar 95 06:52:25 -0600; AA10868 Received: from bilby.cs.uwa.oz.au by cs.wisc.edu; Thu, 2 Mar 95 06:52:21 -0600 Received: from (mafm@parma.cs.uwa.oz.au [130.95.1.7]) by cs.uwa.oz.au (8.6.8/8.5) with SMTP id QAA19416; Thu, 2 Mar 1995 16:03:40 +0800 Message-Id: <199503020803.QAA19416@cs.uwa.oz.au> From: schlimme@eecs.wsu.edu (Jeffrey C. Schlimmer) To: reinforce@cs.uwa.edu.au (Reinforcement List) Subject: Machine Learning Conference Workshops Date: Wed, 1 Mar 1995 20:04:10 -0800 WORKSHOP CALLS FOR PAPERS Twelfth International Conference on Machine Learning Tahoe City, California, U.S.A. July 9, 1995 AGENTS THAT LEARN FROM OTHER AGENTS Agent-oriented learning is currently receiving a great deal of attention among machine learning researchers. The purpose of this workshop is to draw researchers from diverse areas of machine learning, such as learning in the context of distributed AI, planning and learning, software agents, knowledge acquisition, reinforcement learning, computational learning theory, neural networks, genetic algorithms, explanation-based learning, and multistrategy learning to address the unifying theme of agents that learn from other agents. This workshop is a special opportunity for empirically-oriented machine learning researchers to interact with the theoretical COLT community on a topic of mutual interest. Submission deadline: May 1, 1995. APPLYING MACHINE LEARNING IN PRACTICE The purpose of this workshop is to characterize the expertise used during the application of ML algorithms to real-world problems and, in doing so, to develop a better understanding of how to use ML tools successfully. We solicit descriptions of the expertise exhibited during the complete sequential decision process leading to successful ML applications and a discussion of what guided the decision making and selection of the approaches used at each step. Submission deadline: May 1, 1995. GENETIC PROGRAMMING - FROM THEORY TO REAL-WORLD APPLICATIONS The goal of the workshop is to shed light onto the methodology for understanding, explaining and controlling GP search and to show how these issues are reflected in GP frameworks and successful or innovative applications. Submission deadline: April 24, 1995. LEARNING FROM EXAMPLES VERSUS PROGRAMMING BY DEMONSTRATION Inductive Learning from Examples (LfE) is a well established subject in Machine Learning. "Pure" LfE is performed automatically without any human interaction. Programming by Demonstration (PbD) on the other hand can be seen as some kind of "extreme" form of user-supported LfE where the user continually interacts with a PbD system. The nearly exclusive focus of it is the learning of programs. PbD researchers have been disappointed with standard ML algorithms. They require too many examples or too strong a domain theory. Moreover they do not learn "useful" concepts that deterministically generate or modify data, but rather learn how to classify. Finally they easily get out of the user's control. Submission deadline: April 7, 1995. VALUE FUNCTION APPROXIMATION IN REINFORCEMENT LEARNING This workshop will explore the issues that arise in reinforcement learning when the value function cannot be learned exactly, but must be approximated. It has long been recognized that approximation is essential on large, real-world problems because the state space is too large to permit table-lookup approaches. In addition, we need to generalize from past experiences to future ones, which inevitably involves making approximations. In principle, all methods for learning from examples are relevant here, but in practice only a few have been tried, and fewer still have been effective. The objective of this workshop is to bring together all the strands of reinforcement learning research that bear directly on the issue of value function approximation in reinforcement learning. We hope to survey what works and what doesn't, and achieve a better understanding of what makes value function approximation special as learning from examples problem. Submission deadline: May 1, 1995. For further information, please consult the conference's World-Wide Web pages in http://www.eecs.wsu.edu/~schlimme/ml95.html . #| Jeffrey C. Schlimmer, Asst. Prof., School of EE & CS, Washington State University, Pullman, WA 99164-2752, (509) 335-2399, (509) 335-3818 FAX http://www.eecs.wsu.edu/~schlimme/ |# From njm@cupido.inesc.pt Thu Mar 2 06:53:01 1995 Received: from cs.wisc.edu by sea.cs.wisc.edu; Thu, 2 Mar 95 06:52:58 -0600; AA10874 Received: from bilby.cs.uwa.oz.au by cs.wisc.edu; Thu, 2 Mar 95 06:52:53 -0600 Received: from (mafm@parma.cs.uwa.oz.au [130.95.1.7]) by cs.uwa.oz.au (8.6.8/8.5) with SMTP id PAA19107; Thu, 2 Mar 1995 15:56:10 +0800 Message-Id: <199503020756.PAA19107@cs.uwa.oz.au> From: njm@cupido.inesc.pt To: reinforce@cs.uwa.edu.au Subject: 2nd CFP: EPIA'95 Date: Wed, 01 Mar 95 16:39:07 +0000 EPIA'95 - 2nd CALL FOR PAPERS SEVENTH PORTUGUESE CONFERENCE ON ARTIFICIAL INTELLIGENCE Funchal, Madeira Island, Portugal October 3-6, 1995 (Under the auspices of the Portuguese Association for AI) SUBMISSION DEADLINE: March 20, 1995 The Seventh Portuguese Conference on Artificial Intelligence (EPIA'95) will be held at Funchal, Madeira Island, Portugal, on October 3-6, 1995. As in previous issues ('89, '91, and '93), EPIA'95 will be run as an international conference, English being the official language. The scientific program encompasses tutorials, invited lectures, demonstrations, and paper presentations. Five well known researchers will present invited lectures. The conference is devoted to all areas of Artificial Intelligence and will cover both theoretical and foundational issues and applications as well. Parallel workshops on Expert Systems, Fuzzy Logic and Neural Networks, and Applications of A.I. to Robotics and Vision Systems will run simultaneously (see below). INVITED LECTURERS ~~~~~~~~~~~~~~~~~ In this issue of the conference,four special invited lectures will promote a debate on the very foundations of Artificial Intelligence, its approaches and results. It is an honour to announce the invited lecturers and the corresponding talks: "Why Human Brains Can't Really Think", by Marvin Minsky (MIT-USA); "Planning and Learning in Intelligent Agents", by Manuela Veloso (CMU-USA); "The Connectionist Paradigm and AI", by Borges de Almeida (IST-Portugal); "The Evolutionist Approach - Past, Present, and Future of AI", by Rodney Brooks (MIT-USA). TUTORIALS ~~~~~~~~~ In this issue of the conference, four tutorials will be delivered: "Artificial Life and Autonomous Robots", by Luc Steels (VUB AI Lab-Belgium); "Virtual Reality - The AI perspective", by David Hogg (Univ. of Leeds-UK); "Introduction to Artificial Intelligence", by Ernesto Costa (Univ. of Coimbra-Portugal); (in Portuguese) "Design of Expert Systems", by Ernesto Morgado (IST-Portugal); (in Portuguese) SUBMISSION OF PAPERS ~~~~~~~~~~~~~~~~~~~~ Authors must submit five (5) complete printed copies of their papers to the "EPIA'95 submission address". Fax or electronic submissions will not be accepted. Submissions must be printed on A4 or 8 1/2"x11" paper using 12 point type. Each page must have a maximum of 38 lines and an average of 75 characters per line (corresponding to the LaTeX article-style, 12 point). Double-sided printing is strongly encouraged. The body of submitted papers must be at most 12 pages, including title, abstract, figures, tables, and diagrams, but excluding the title page and bibliography. ELECTRONIC ABSTRACT ~~~~~~~~~~~~~~~~~~~ In addition to submitting the paper copies, authors should send to epia95-abstracts@inesc.pt a short (200 words) electronic abstract of their paper to aid the reviewing process. The electronic abstract must be in plain ASCII text (no LaTeX)) in the following format: TITLE: FIRST AUTHOR: <last name, first name> EMAIL: <email of the first author> FIRST ADDRESS: <first author address> COAUTHORS: <their names, if any> KEYWORDS: <keywords separated by commas> ABSTRACT: <text of the abstract> Authors are requested to select 1-3 appropriate keywords from the list below. Authors are welcome to add additional keywords descriptors as needed. Applications, agent-oriented programming, automated reasoning, belief revision, case-based reasoning, common sense reasoning, constraint satisfaction, distributed AI, expert systems, genetic algorithms, knowledge representation, logic programming, machine learning, natural language understanding, nonmonotonic reasoning, planning, qualitative reasoning, real-time systems, robotics, spatial reasoning, theorem proving, theory of computation, tutoring systems. REVIEW OF PAPERS ~~~~~~~~~~~~~~~~ Submissions will be judged on significance, originality, quality and clarity. Reviewing will be blind to the identities of the authors. This requires that authors exercise some care not to identify themselves in their papers. Each copy of the paper must have a title page, separated from the body of the paper, including the title of the paper, the names and addresses of all authors, a list of content areas (see above) and any acknowledgments. The second page should include the same title, a short abstract of less than 200 words, and the exact same contents areas, but not the names nor affiliations of the authors. This page may include text of the paper. The references should include all published literature relevant to the paper, including previous works of the authors, but should not include unpublished works of the authors. When referring to one's own work, use the third person. For example, say "previously, Peter [17] has shown that ...". Try to avoid including any information in the body of the paper or references that would identify the authors or their institutions. Such information can be added to the final camera-ready version for publication. Please do not staple the title page to the body of the paper. Submitted papers must be unpublished. PUBLICATION ~~~~~~~~~~~ The proceedings will be published by Springer-Verlag (lecture notes in A.I. series). Authors will be required to transfer copyright of their paper to Springer-Verlag. ASSOCIATED WORKSHOPS ~~~~~~~~~~~~~~~~~~~~ In the framework of the conference three workshops will be organized: Applications of Expert Systems, Fuzzy Logic and Neural Networks in Engineering, and Applications of Artificial Intelligence to Robotics and Vision Systems. Real world applications, running systems, and demos are welcome. CONFERENCE & PROGRAM CO-CHAIRS ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Carlos Pinto-Ferreira Nuno Mamede Instituto Superior Tecnico Instituto Superior Tecnico ISR, Av. Rovisco Pais INESC, Apartado 13069 1000 Lisboa, Portugal 1000 Lisboa, Portugal Voice: +351 (1) 8475105 Voice: +351 (1) 310-0234 Fax: +351 (1) 3523014 Fax: +351 (1) 525843 Email: cpf@kappa.ist.utl.pt Email: njm@inesc.pt PROGRAM COMMITTEE ~~~~~~~~~~~~~~~~~ Antonio Porto (Portugal) Lauiri Carlson (Finland) Benjamin Kuipers (USA) Luc Steels (Belgium) Bernhard Nebel (Germany) Luigia Aiello (Italy) David Makinson (Germany) Luis Moniz Pereira (Portugal) Erik Sandewall (Sweden) Luis Monteiro (Portugal) Ernesto Costa (Portugal) Manuela Veloso (USA) Helder Coelho (Portugal) Maria Cravo (Portugal) Joao Martins (Portugal) Miguel Filgueiras (Portugal) John Self (UK) Yoav Shoham (USA) Jose Carmo (Portugal) Yves Kodratoff (France) DEADLINES ~~~~~~~~~ Papers Submission: ................. March 20, 1995 Notification of acceptance: ........ May 15, 1995 Camera Ready Copies Due: ........... June 12, 1995 SUBMISSION & INQUIRIES ADDRESS ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ EPIA95 INESC, Apartado 13069 1000 Lisboa, Portugal Voice: +351 (1) 310-0325 Fax: +351 (1) 525843 Email: epia95@inesc.pt SUPPORTERS ~~~~~~~~~~ Banco Nacional Ultramarino Governo Regional da Madeira Instituto Superior Tecnico SISCOG - Sistemas Cognitivos INESC CITMA IBM TAPair Portugal PLANNING TO ATTEND ~~~~~~~~~~~~~~~~~~ People planning to submit a paper or/and to attend the conference or attend a workshop are asked to complete and return the following form (by fax or email) to the inquiries address standing their intention. It will help the conference organizers to estimate the facilities needed for the conference and will enable all interested people to receive updated information. +----------------------------------------------------------------+ | REGISTRATION OF INTEREST | | | | Title . . . . . Name . . . . . . . . . . . . . . . . . . . . | | Institution . . . . . . . . . . . . . . . . . . . . . . . . . | | Address1 . . . . . . . . . . . . . . . . . . . . . . . . . . . | | Address2 . . . . . . . . . . . . . . . . . . . . . . . . . . . | | Country . . . . . . . . . . . . . . . . . . . . . . . . . . . | | Telephone. . . . . . . . . . . . . . . Fax . . . . . . . . . . | | Email address. . . . . . . . . . . . . . . . . . . . . . . . . | | I intend to submit a paper (yes/no). . . . . . . . . . . . . . | | I intend to participate only (yes/no). . . . . . . . . . . . . | | I will travel with ... guests | +----------------------------------------------------------------+ From njm@cupido.inesc.pt Thu Mar 2 07:20:24 1995 Received: from cs.wisc.edu by sea.cs.wisc.edu; Thu, 2 Mar 95 07:20:22 -0600; AA11963 Received: from bilby.cs.uwa.oz.au by cs.wisc.edu; Thu, 2 Mar 95 07:20:17 -0600 Received: from (mafm@parma.cs.uwa.oz.au [130.95.1.7]) by cs.uwa.oz.au (8.6.8/8.5) with SMTP id PAA19132; Thu, 2 Mar 1995 15:57:48 +0800 Message-Id: <199503020757.PAA19132@cs.uwa.oz.au> From: njm@cupido.inesc.pt To: reinforce@cs.uwa.edu.au Subject: 2nd CFP: EPIA'95 (LaTeX) Date: Wed, 01 Mar 95 16:39:12 +0000 \documentstyle{article} \setlength{\topmargin}{-1.2in} \setlength{\oddsidemargin}{-0.5in} \setlength{\evensidemargin}{-0.5in} \setlength{\textwidth}{7.5in} \setlength{\textheight}{10.5in} \begin{document} %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % The next two lines define a new length ``\helpTwoColumn'' % used when it is necessary to use a twocolumn output format, % namely in the Program co-chairs and program committee sections. % \newlength{\helpTwoColumn} \settowidth{\helpTwoColumn}{Email: {\tt cpf@kappa.ist.utl.pt}} %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \begin{center} {\Large \bf EPIA'95 - CALL FOR PAPERS}\\ \bigskip {\large \bf SEVENTH PORTUGUESE CONFERENCE\\ ON\\ ARTIFICIAL INTELLIGENCE}\\ \bigskip {\bf Funchal, Madeira Island, Portugal \\ October 3-6, 1995}\\ \medskip (Under the auspices of the Portuguese Association for AI) \end{center} \medskip \noindent The Seventh Portuguese Conference on Artificial Intelligence (EPIA'95) will be held at Funchal, Madeira Island, Portugal, on October 3-6, 1995. As in previous issues ('89, '91, and '93), EPIA'95 will be run as an international conference, English being the official language. The scientific program encompasses tutorials, invited lectures, demonstrations, and paper presentations. Five well known researchers will present invited lectures. The conference is devoted to all areas of Artificial Intelligence and will cover both theoretical and foundational issues and applications as well. Parallel workshops on Expert Systems, Fuzzy Logic and Neural Networks, and Applications of A.I. to Robotics and Vision Systems will run simultaneously (see below). \subsubsection*{Invited Lecturers} In this issue of the conference, four special invited lectures will promote a debate on the very foundations of Artificial Intelligence, its approaches and results. It is an honour to announce the invited lecturers and the corresponding talks: \vspace*{-\medskipamount} \begin{center} "Why Human Brains Can't Really Think", by Marvin Minsky (MIT-USA); \\ "Planning and Learning in Intelligent Agents", by Manuela Veloso (CMU-USA); \\ "The Connectionist Paradigm and AI", by Lu\'{\i}s Borges de Almeida (IST-Portugal);\\ "The Evolutionist Approach - Past, Present, and Future of AI", by Rodney Brooks (MIT-USA). \end{center} \subsubsection*{Tutorials} In this issue of the conference, four tutorials will be delivered: \vspace*{-\medskipamount} \begin{center} "Artificial Life and Autonomous Robots", by Luc Steels (VUB AI Lab-Belgium); \\ "Virtual Reality - The AI perspective", by David Hogg (Univ. of Leeds-UK);\\ "Introduction to Artificial Intelligence", by Ernesto Costa (Univ. of Coimbra-Portugal); (in Portuguese)\\ "Design of Expert Systems", by Ernesto Morgado (IST-Portugal); (in Portuguese) \end{center} \subsubsection*{Submission of Papers} Authors must submit five (5) complete printed copies of their papers to the ``EPIA'95 submission address". Fax or electronic submissions will not be accepted. Submissions must be printed on $A4$ or $8\: 1/2'' \times 11''$ paper using 12 point type. Each page must have a maximum of 38 lines and an average of 75 characters per line (corresponding to the \LaTeX\ article-style, 12 point). Double-sided printing is strongly encouraged. The body of submitted papers must be at most 12 pages, including title, abstract, figures, tables, and diagrams, but excluding the title page and bibliography. \subsubsection*{Electronic Abstract} \begin{sloppypar} In addition to submitting the paper copies, authors should send to Co{\tt epia95-abstracts@inesc.pt} a short (200 words) electronic abstract of their paper to aid the reviewing process. The electronic abstract must be in plain ASCII text (no LaTeX)) in the following format: \end{sloppypar} \indent\indent TITLE: {\tt <title of the paper>}\\ \indent\indent FIRST AUTHOR: {\tt <last name, first name>}\\ \indent\indent EMAIL: {\tt <email of the first author>}\\ \indent\indent FIRST ADDRESS: {\tt <first author address>}\\ \indent\indent COAUTHORS: {\tt <their names, if any>}\\ \indent\indent KEYWORDS: {\tt <keywords separated by commas>}\\ \indent\indent ABSTRACT: {\tt <text of the abstract>}\\ Authors are requested to select 1-3 appropriate keywords from the list below. Authors are welcome to add additional keywords descriptors as needed. Applications, agent-oriented programming, automated reasoning, belief revision, case-based reasoning, common sense reasoning, constraint satisfaction, distributed AI, expert systems, genetic algorithms, knowledge representation, logic programming, machine learning, natural language understanding, nonmonotonic reasoning, planning, qualitative reasoning, real-time systems, robotics, spatial reasoning, theorem proving, theory of computation, tutoring systems. \subsubsection*{Review of Papers} Submissions will be judged on significance, originality, quality and clarity. Reviewing will be blind to the identities of the authors. This requires that authors exercise some care not to identify themselves in their papers. Each copy of the paper must have a title page, separated from the body of the paper, including the title of the paper, the names and addresses of all authors, a list of content areas (see above) and any acknowledgments. The second page should include the same title, a short abstract of less than 200 words, and the exact same contents areas, but not the names nor affiliations of the authors. This page may include text of the paper. The references should include all published literature relevant to the paper, including previous works of the authors, but should not include unpublished works of the authors. When referring to one's own work, use the third person. For example, say ``previously, Peter [17] has shown that ...". Try to avoid including any information in the body of the paper or references that would identify the authors or their institutions. Such information can be added to the final camera-ready version for publication. Please do not staple the title page to the body of the paper. Submitted papers must be unpublished. \subsubsection*{Publication} The proceedings will be published by Springer-Verlag (lecture notes in A.I. series). Authors will be required to transfer copyright of their paper to Springer-Verlag. \subsubsection*{Associated Workshops} In the framework of the conference three workshops will be organized: Applications of Expert Systems, Fuzzy Logic and Neural Networks in Engineering, and Applications of Artificial Intelligence to Robotics and Vision Systems. Real world applications, running systems, and demos are welcome. \subsubsection*{Planning to Attend} People planning to submit a paper or/and to attend the conference or attend a workshop are asked to send a note (inquiries address) standing their intention, as early as possible, to the conference organizers, in order to estimate the facilities needed for the conference. \subsubsection*{Conference \& Program -Chairs} \hfill \parbox{\helpTwoColumn}{ Carlos Pinto-Ferreira\\ Instituto Superior Tecnico\\ ISR, Av. Rovisco Pais\\ 1000 Lisboa, Portugal\\ Voice: +351 (1) 8475105\\ Fax: +351 (1) 3523014\\ Email: {\tt cpf@kappa.ist.utl.pt}} \hfill \parbox{\helpTwoColumn}{ Nuno Mamede\\ Instituto Superior Tecnico\\ INESC, Apartado 13069\\ 1000 Lisboa, Portugal\\ Voice: +351 (1) 310-0234\\ Fax: +351 (1) 525843\\ Email: {\tt njm@inesc.pt}} \hfill\ \subsubsection*{Program Committee} \hfill \parbox{\helpTwoColumn}{ Ant\'{o}nio Porto (Portugal)\\ Benjamin Kuipers (USA) \\ Bernhard Nebel (Germany)\\ David Makinson (Germany)\\ Erik Sandewall (Sweden) \\ Ernesto Costa (Portugal)\\ Helder Coelho (Portugal)\\ Jo\~{a}o Martins (Portugal) \\ John Self (UK) \\ Jos\'{e} Carmo (Portugal)} \hfill \parbox{\helpTwoColumn}{ Lauiri Carlson (Finland)\\ Luc Steels (Belgium)\\ Luigia Aiello (Italy)\\ Lu\'{\i}s Moniz Pereira (Portugal)\\ Lu\'{\i}s Monteiro (Portugal)\\ Manuela Veloso (USA)\\ Maria Cravo (Portugal)\\ Miguel Filgueiras (Portugal)\\ Yoav Shoham (USA)\\ Yves Kodratoff (France)} \hfill\ \subsubsection*{Deadlines} Papers due: March 20, 1995\\ Author notification: May 15, 1995\\ Papers returned: June 12, 1995 \newpage \subsubsection*{Submission \& Inquiries Address} EPIA95\\ INESC, Apartado 13069\\ 1000 Lisboa, Portugal\\ Voice: +351 (1) 310-0325\\ Fax: +351 (1) 525843\\ Email: {\tt epia95@inesc.pt} \subsubsection*{Supporters} \hfill \parbox{\helpTwoColumn}{ Banco Nacional Ultramarino\\ Instituto Superior Tecnico\\ INESC\\ IBM} \hfill \parbox{\helpTwoColumn}{ Governo Regional da Madeira\\ SISCOG - Sistemas Cognitivos\\ CITMA\\ TAPair Portugal} \hfill\ \end{document} From Connectionists-Request@cs.cmu.edu Thu Mar 2 13:13:09 1995 Received: from cs.wisc.edu by sea.cs.wisc.edu; Thu, 2 Mar 95 13:13:06 -0600; AA15200 Received: from TELNET-1.SRV.CS.CMU.EDU by cs.wisc.edu; Thu, 2 Mar 95 13:12:53 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id ab01684; 1 Mar 95 14:31:13 EST Received: from GS151.SP.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa01667; 1 Mar 95 14:08:19 EST Received: from GS151.SP.CS.CMU.EDU by GS151.SP.CS.CMU.EDU id aa26652; 1 Mar 95 14:07:06 EST Received: from B.GP.CS.CMU.EDU by B.GP.CS.CMU.EDU id aa00837; 1 Mar 95 0:06:08 EST To: Connectionists@cs.cmu.edu From: Connectionists-Request@cs.cmu.edu Subject: Bi-monthly Reminder Date: Wed, 01 Mar 95 00:06:00 EST Message-Id: <835.794034360@B.GP.CS.CMU.EDU> Sender: Connectionist_Research_Group@B.GP.CS.CMU.EDU *** DO NOT FORWARD TO ANY OTHER LISTS *** This note was last updated September 9, 1994. This is an automatically posted bi-monthly reminder about how the CONNECTIONISTS list works and how to access various online resources. CONNECTIONISTS is a moderated forum for enlightened technical discussions and professional announcements. It is not a random free-for-all like comp.ai.neural-nets. Membership in CONNECTIONISTS is restricted to persons actively involved in neural net research. The following posting guidelines are designed to reduce the amount of irrelevant messages sent to the list. Before you post, please remember that this list is distributed to thousands of busy people who don't want their time wasted on trivia. Also, many subscribers pay cash for each kbyte; they shouldn't be forced to pay for junk mail. -- Dave Touretzky & Lisa Saksida --------------------------------------------------------------------- What to post to CONNECTIONISTS ------------------------------ - The list is primarily intended to support the discussion of technical issues relating to neural computation. - We encourage people to post the abstracts of their latest papers and tech reports. - Conferences and workshops may be announced on this list AT MOST twice: once to send out a call for papers, and once to remind non-authors about the registration deadline. A flood of repetitive announcements about the same conference is not welcome here. - Requests for ADDITIONAL references. This has been a particularly sensitive subject. Please try to (a) demonstrate that you have already pursued the quick, obvious routes to finding the information you desire, and (b) give people something back in return for bothering them. The easiest way to do both these things is to FIRST do the library work to find the basic references, then POST these as part of your query. Here's an example: WRONG WAY: "Can someone please mail me all references to cascade correlation?" RIGHT WAY: "I'm looking for references to work on cascade correlation. I've already read Fahlman's paper in NIPS 2, his NIPS 3 abstract, corresponded with him directly and retrieved the code in the nn-bench archive. Is anyone aware of additional work with this algorithm? I'll summarize and post results to the list." - Announcements of job openings related to neural computation. - Short reviews of new textbooks related to neural computation. To send mail to everyone on the list, address it to Connectionists@CS.CMU.EDU ------------------------------------------------------------------- What NOT to post to CONNECTIONISTS: ----------------------------------- - Requests for addition to the list, change of address and other administrative matters should be sent to: "Connectionists-Request@cs.cmu.edu" (note the exact spelling: many "connectionists", one "request"). If you mention our mailing list to someone who may apply to be added to it, please make sure they use the above and NOT "Connectionists@cs.cmu.edu". - Requests for e-mail addresses of people who are believed to subscribe to CONNECTIONISTS should be sent to postmaster@appropriate-site. If the site address is unknown, send your request to Connectionists-Request@cs.cmu.edu and we'll do our best to help. A phone call to the appropriate institution may sometimes be simpler and faster. - Note that in many mail programs a reply to a message is automatically "CC"-ed to all the addresses on the "To" and "CC" lines of the original message. If the mailer you use has this property, please make sure your personal response (request for a Tech Report etc.) is NOT broadcast over the net. ------------------------------------------------------------------------------- The CONNECTIONISTS Archive: --------------------------- All e-mail messages sent to "Connectionists@cs.cmu.edu" starting 27-Feb-88 are now available for public perusal. A separate file exists for each month. The files' names are: arch.yymm where yymm stand for the obvious thing. Thus the earliest available data are in the file: arch.8802 Files ending with .Z are compressed using the standard unix compress program. To browse through these files (as well as through other files, see below) you must FTP them to your local machine. The file "current" in the same directory contains the archives for the current month. ------------------------------------------------------------------------------- How to FTP Files from the CONNECTIONISTS Archive ------------------------------------------------ 1. Open an FTP connection to host B.GP.CS.CMU.EDU 2. Login as user anonymous with password your username. 3. 'cd' directly to the following directory: /afs/cs/project/connect/connect-archives The archive directory is the ONLY one you can access. You can't even find out whether any other directories exist. If you are using the 'cd' command you must cd DIRECTLY into this directory. Problems? - contact us at "Connectionists-Request@cs.cmu.edu". ------------------------------------------------------------------------------- Using Mosaic and the World Wide Web ----------------------------------- You can also access these files using the following url: http://www.cs.cmu.edu:8001/afs/cs/project/connect/connect-archives ---------------------------------------------------------------------- The NEUROPROSE Archive ---------------------- Anonymous FTP on archive.cis.ohio-state.edu (128.146.8.52) pub/neuroprose directory This directory contains technical reports as a public service to the connectionist and neural network scientific community which has an organized mailing list (for info: connectionists-request@cs.cmu.edu) Researchers may place electronic versions of their preprints in this directory, announce availability, and other interested researchers can rapidly retrieve and print the postscripts. This saves copying, postage and handling, by having the interested reader supply the paper. We strongly discourage the merger into the repository of existing bodies of work or the use of this medium as a vanity press for papers which are not of publication quality. PLACING A FILE To place a file, put it in the Inbox subdirectory, and send mail to pollack@cis.ohio-state.edu. Within a couple of days, I will move and protect it, and suggest a different name if necessary. Current naming convention is author.title.filetype.Z where title is just enough to discriminate among the files of the same author. The filetype is usually "ps" for postscript, our desired universal printing format, but may be tex, which requires more local software than a spooler. The Z indicates that the file has been compressed by the standard unix "compress" utility, which results in the .Z affix. To place or retrieve .Z files, make sure to issue the FTP command "BINARY" before transfering files. After retrieval, call the standard unix "uncompress" utility, which removes the .Z affix. An example of placing a file is in the appendix. Make sure your paper is single-spaced, so as to save paper, and include an INDEX Entry, consisting of 1) the filename, 2) the email contact for problems, 3) the number of pages and 4) a one sentence description. See the INDEX file for examples. ANNOUNCING YOUR PAPER It is the author's responsibility to invite other researchers to make copies of their paper. Before announcing, have a friend at another institution retrieve and print the file, so as to avoid easily found local postscript library errors. And let the community know how many pages to expect on their printer. Finally, information about where the paper will/might appear is appropriate inside the paper as well as in the announcement. In your subject line of your mail message, rather than "paper available via FTP," please indicate the subject or title, e.g. "paper available "Solving Towers of Hanoi with ART-4" Please add two lines to your mail header, or the top of your message, so as to facilitate the development of mailer scripts and macros which can automatically retrieve files from both NEUROPROSE and other lab-specific repositories: FTP-host: archive.cis.ohio-state.edu FTP-filename: /pub/neuroprose/filename.ps.Z When you announce a paper, you should consider whether (A) you want it automatically forwarded to other groups, like NEURON-DIGEST, (which gets posted to comp.ai.neural-networks) and if you want to provide (B) free or (C) prepaid hard copies for those unable to use FTP. To prevent forwarding, place a "**DO NOT FORWARD TO OTHER GROUPS**" at the top of your file. If you do offer hard copies, be prepared for a high cost. One author reported that when they allowed combination AB, the rattling around of their "free paper offer" on the worldwide data net generated over 2000 hardcopy requests! A shell script called Getps, written by Tony Plate, is in the directory, and can perform the necessary retrieval operations, given the file name. Functions for GNU Emacs RMAIL, and other mailing systems will also be posted as debugged and available. At any time, for any reason, the author may request their paper be updated or removed. For further questions contact: Jordan Pollack Associate Professor Computer Science Department Center for Complex Systems Brandeis University Phone: (617) 736-2713/* to fax Waltham, MA 02254 email: pollack@cs.brandeis.edu APPENDIX: Here is an example of naming and placing a file: unix> compress myname.title.ps unix> ftp archive.cis.ohio-state.edu Connected to archive.cis.ohio-state.edu. 220 archive.cis.ohio-state.edu FTP server ready. Name: anonymous 331 Guest login ok, send ident as password. Password:neuron 230 Guest login ok, access restrictions apply. ftp> binary 200 Type set to I. ftp> cd pub/neuroprose/Inbox 250 CWD command successful. ftp> put myname.title.ps.Z 200 PORT command successful. 150 Opening BINARY mode data connection for myname.title.ps.Z 226 Transfer complete. 100000 bytes sent in 1.414 seconds ftp> quit 221 Goodbye. unix> mail pollack@cis.ohio-state.edu Subject: file in Inbox. Jordan, I just placed the file myname.title.ps.Z in the Inbox. Here is the INDEX entry: myname.title.ps.Z mylogin@my.email.address 12 pages. A random paper which everyone will want to read Let me know when it is in place so I can announce it to Connectionists@cmu. ^D AFTER RECEIVING THE GO-AHEAD, AND HAVING A FRIEND TEST RETRIEVE THE FILE, HE DOES THE FOLLOWING: unix> mail connectionists Subject: TR announcement: Born Again Perceptrons FTP-host: archive.cis.ohio-state.edu FTP-file: pub/neuroprose/myname.title.ps.Z The file myname.title.ps.Z is now available for copying from the Neuroprose repository: Random Paper (12 pages) Somebody Somewhere Cornell University ABSTRACT: In this unpublishable paper, I generate another alternative to the back-propagation algorithm which performs 50% better on learning the exclusive-or problem. ~r.signature ^D ------------------------------------------------------------------------ How to FTP Files from the NN-Bench Collection --------------------------------------------- 1. Create an FTP connection from wherever you are to machine "ftp.cs.cmu.edu" (128.2.254.155). 2. Log in as user "anonymous" with password your username. 3. Change remote directory to "/afs/cs/project/connect/bench". Any subdirectories of this one should also be accessible. Parent directories should not be. Another valid directory is "/afs/cs/project/connect/code", where we store various supported and unsupported neural network simulators and related software. 4. At this point FTP should be able to get a listing of files in this directory and fetch the ones you want. Problems? - contact us at "neural-bench@cs.cmu.edu". From jari@vermis.hut.fi Thu Mar 2 13:13:14 1995 Received: from cs.wisc.edu by sea.cs.wisc.edu; Thu, 2 Mar 95 13:13:10 -0600; AA15206 Received: from TELNET-1.SRV.CS.CMU.EDU by cs.wisc.edu; Thu, 2 Mar 95 13:13:07 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id ac01684; 1 Mar 95 14:32:09 EST Received: from GS151.SP.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id ab01667; 1 Mar 95 14:08:21 EST Received: from GS151.SP.CS.CMU.EDU by GS151.SP.CS.CMU.EDU id aa26655; 1 Mar 95 14:07:28 EST Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa02252; 1 Mar 95 2:41:51 EST Received: from santra.hut.fi by CS.CMU.EDU id aa07158; 1 Mar 95 2:40:38 EST Received: from vermis (vermis.hut.fi [130.233.168.57]) by santra.hut.fi (8.6.8.1/8.6.7) with ESMTP id JAA25072 for <@hut.fi:Connectionists@CS.CMU.EDU>; Wed, 1 Mar 1995 09:40:33 +0200 Received: by vermis (950215.SGI.8.6.10/930416.SGI) id JAA16971; Wed, 1 Mar 1995 09:46:28 +0200 Date: Wed, 1 Mar 1995 09:46:28 +0200 From: Jari Kangas <jari@vermis.hut.fi> Message-Id: <199503010746.JAA16971@vermis> To: Connectionists@cs.cmu.edu Subject: New version (v3.0) of SOM_PAK Reply-To: Jari.Kangas@hut.fi ************************************************************************ * * * SOM_PAK * * * * The * * * * Self-Organizing Map * * * * Program Package * * * * Version 3.0 (March 1, 1995) * * * * Prepared by the * * SOM Programming Team of the * * Helsinki University of Technology * * Laboratory of Computer and Information Science * * Rakentajanaukio 2 C, SF-02150 Espoo * * FINLAND * * * * Copyright (c) 1992-1995 * * * ************************************************************************ Updated public-domain programs for Self-Organizing Map (SOM) algorithms are available via anonymous FTP on the Internet. A new book on SOM and LVQ (Learning Vector Quantization) has also recently come out: Teuvo Kohonen. Self-Organizing Maps (Springer Series in Information Science, Vol 30, 1995). In short, Self-Organizing Map (SOM) defines a 'nonlinear projection' of the probability density function of the high-dimensional input data onto the two-dimensional display. SOM places a number of reference vectors into an input data space to approximate to its data set in an ordered fashion, and thus implements a kind of nonparametric, nonlinear regression. This package contains all necessary programs for the application of Self-Organizing Map algorithms in an arbitrary complex data visualization task. This code is distributed without charge on an "as is" basis. There is no warranty of any kind by the authors or by Helsinki University of Technology. In the implementation of the SOM programs we have tried to use as simple code as possible. Therefore the programs are supposed to compile in various machines without any specific modifications made on the code. All programs have been written in ANSI C. The programs are available in two archive formats, one for the UNIX-environment, the other for MS-DOS. Both archives contain exactly the same files. These files can be accessed via FTP as follows: 1. Create an FTP connection from wherever you are to machine "cochlea.hut.fi". The internet address of this machine is 130.233.168.48, for those who need it. 2. Log in as user "anonymous" with your own e-mail address as password. 3. Change remote directory to "/pub/som_pak". 4. At this point FTP should be able to get a listing of files in this directory with DIR and fetch the ones you want with GET. (The exact FTP commands you use depend on your local FTP program.) Remember to use the binary transfer mode for compressed files. The som_pak program package includes the following files: - Documentation: README short description of the package and installation instructions som_doc.ps documentation in (c) PostScript format som_doc.ps.Z same as above but compressed som_doc.txt documentation in ASCII format - Source file archives: som_p3r0.exe Self-extracting MS-DOS archive file som_pak-3.0.tar UNIX tape archive file som_pak-3.0.tar.Z same as above but compressed An example of FTP access is given below unix> ftp cochlea.hut.fi (or 130.233.168.48) Name: anonymous Password: <your email address> ftp> cd /pub/som_pak ftp> binary ftp> get som_pak-3.0.tar.Z ftp> quit unix> uncompress som_pak-3.0.tar.Z unix> tar xvfo som_pak-3.0.tar See file README for further installation instructions. All comments concerning this package should be addressed to som@cochlea.hut.fi. ************************************************************************ From bishopc@helios.aston.ac.uk Thu Mar 2 13:13:19 1995 Received: from cs.wisc.edu by sea.cs.wisc.edu; Thu, 2 Mar 95 13:13:13 -0600; AA15212 Received: from TELNET-1.SRV.CS.CMU.EDU by cs.wisc.edu; Thu, 2 Mar 95 13:13:10 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id ad01684; 1 Mar 95 14:32:58 EST Received: from GS151.SP.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id ac01667; 1 Mar 95 14:08:35 EST Received: from GS151.SP.CS.CMU.EDU by GS151.SP.CS.CMU.EDU id aa26658; 1 Mar 95 14:07:56 EST Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa02601; 1 Mar 95 3:27:24 EST Received: from sun2.nsfnet-relay.ac.uk by CS.CMU.EDU id aa07415; 1 Mar 95 3:26:56 EST Via: uk.ac.aston; Wed, 1 Mar 1995 08:26:30 +0000 Received: from synapse by email.aston.ac.uk with SMTP (PP) id <05478-0@email.aston.ac.uk>; Wed, 1 Mar 1995 08:23:17 +0000 From: bishopc <bishopc@helios.aston.ac.uk> Date: Wed, 1 Mar 1995 08:29:38 +0000 Message-Id: <14359.9503010829@sun.aston.ac.uk> To: Connectionists@cs.cmu.edu Subject: NCAF Spring Conference Cc: c.m.bishop@aston.ac.uk X-Sun-Charset: US-ASCII Content-Length: 3740 -------------------------------------------------------------------- NEURAL COMPUTING APPLICATIONS FORUM NCAF Two-Day Conference: "Practical Applications and Techniques of Neural Networks" (sponsored by IBM and Neuroptics) 12 and 13 April, 1995 Robinson College, Cambridge, UK 12 April 1995 ------------- Invited Guest Tutorial: Pattern Recognition Using Hidden Markov Models Prof Steve Young, Cambridge University Keynote Talk: The IBM ZISC Chip Guy Paillet, Neuroptics Consulting Neural Computing: The Key Answers? Prof David Bounds, Aston University (EPSRC Neural Computing Coordinator) Neural Networks for Analysis of EEG David Siegwart, Oxford University High Speed Car Number Plate Recognition (with demonstration!) Steve Gull, Cambridge University Workshop: Practicalities of Training Networks An interactive workshop with opportunities for questions and discussion from the audience. Champagne Reception hosted by Neuroptics and IBM The ZISC Banquet After dinner speaker: Robert Worden, Logica Cambridge 13 April 1995 ------------- Neural Interpretation of Foetal Heart Rate Traces Richard Shaw, Cambridge University Classification of Wood Quality John Keating, St Patrick's, Ireland Medical Diagnosis Using ARTMap for Autonomous Learning Robert Harrison, Sheffield University Control of a Jet Engine Ian Nabney, Aston University Detection of Organised Credit Card Fraud Iain Strachan, AEA Technology Recurrent Networks for Very Large Vocabulary Speech Recognition Tony Robinson, Cambridge University Interpretation and Knowledge Discovery in MLPs Marilyn Vaughn, RMCS, Cranfield University Solving Folding Optimisation Problems with Self-Organising Networks Shara Amin, British Telecom Using Neural Networks for Property Valuation Howard James, Portsmouth University An Evaluation of the Neocognitron David Lovell, Cambridge University ------------------------------------------------------------------- NEURAL COMPUTING APPLICATIONS FORUM The Neural Computing Applications Forum (NCAF) was formed in 1990 and has since come to provide the principal mechanism for exchange of ideas and information between academics and industrialists in the UK on all aspects of neural networks and their practical applications. NCAF organises four 2-day conferences each year, which are attended by well over 100 participants. It has its own international journal `Neural Computing and Applications' which is published quarterly by Springer-Verlag, and it produces a quarterly newsletter `Networks'. Annual membership rates (Pounds Stirling): Company: 300 Individual: 170 Associate 110 Student: 65 Membership includes free registration at all four annual conferences, a subscription to the journal `Neural Computing and Applications', and a subscription to `Networks'. Associate membership includes the journal and newsletter but does not include admission to the conferences (for which a separate fee must be paid) and is intended primarily for overseas members who are unable to attend most of the conferences. For further information: Tel: +44 (0)784 477271 Fax: +44 (0)784 472879 Chris M Bishop (Chairman, NCAF) -------------------------------------------------------------------- Professor Chris M Bishop Tel. +44 (0)21 359 3611 x4270 Neural Computing Research Group Fax. +44 (0)21 333 6215 Dept. of Computer Science c.m.bishop@aston.ac.uk Aston University Birmingham B4 7ET, UK -------------------------------------------------------------------- From jbaxter@colossus.cs.adelaide.edu.au Thu Mar 2 13:13:21 1995 Received: from cs.wisc.edu by sea.cs.wisc.edu; Thu, 2 Mar 95 13:13:16 -0600; AA15217 Received: from TELNET-1.SRV.CS.CMU.EDU by cs.wisc.edu; Thu, 2 Mar 95 13:13:13 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id ae01684; 1 Mar 95 14:33:27 EST Received: from GS151.SP.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id ad01667; 1 Mar 95 14:08:50 EST Received: from GS151.SP.CS.CMU.EDU by GS151.SP.CS.CMU.EDU id aa26661; 1 Mar 95 14:08:05 EST Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa05086; 1 Mar 95 6:54:15 EST Received: from tigger.cs.adelaide.edu.au by CS.CMU.EDU id aa08144; 1 Mar 95 6:53:56 EST Received: from colossus.cs.adelaide.edu.au (via delivery) by tigger.cs.adelaide.edu.au with SMTP (5.65/UA-5.20) id AA05485; Wed, 1 Mar 95 22:23:48 +1030 Received: by colossus.cs.adelaide.edu.au (5.65/SMI-4.1)id AA27533; Wed, 1 Mar 95 22:23:53 +1030 From: Jon Baxter <jbaxter@colossus.cs.adelaide.edu.au> Message-Id: <9503011153.AA27533@colossus.cs.adelaide.edu.au> Subject: Paper Available: The canonical metric in vector quantization To: connectionists@cs.cmu.edu Date: Wed, 1 Mar 1995 22:23:51 +1030 (CST) X-Mailer: ELM [version 2.4 PL21] Mime-Version: 1.0 Content-Type: text/plain; charset=US-ASCII Content-Transfer-Encoding: 7bit Content-Length: 1617 The following paper is available via anonymous ftp from calvin.maths.flinders.edu.au:://pub/jon/quant.ps.Z FTP instructions are given at the end of the message. Title: The Canonical Metric For Vector Quantization, 8 pages. Author: Jonathan Baxter Abstract: To measure the quality of a set of vector quantization points a means of measuring the distance between two points is required. Common metrics such as the {\em Hamming} and {\em Euclidean} metrics, while mathematically simple, are inappropriate for comparing speech signals or images. In this paper it is argued that there often exists a natural {\em environment} of functions to the quantization process (for example, the word classifiers in speech recognition and the character classifiers in character recognition) and that such an enviroment induces a {\em canonical metric} on the space being quantized. It is proved that optimizing the {\em reconstruction error} with respect to the canonical metric gives rise to optimal approximations of the functions in the environment, so that the canonical metric can be viewed as embodying all the essential information relevant to learning the functions in the environment. Techniques for {\em learning} the canonical metric are discussed, in particular the relationship between learning the canonical metric and {\em internal representation learning}. FTP Instructions: unix> ftp calvin.maths.flinders.edu.au (or 129.96.32.2) login: anonymous password: (your e-mail address) ftp> cd pub/jon ftp> binary ftp> get quant.ps.Z ftp> quit unix> uncompress quant.ps.Z unix> lpr quant.ps (or however you print) From ajit@uts.cc.utexas.edu Thu Mar 2 13:13:29 1995 Received: from cs.wisc.edu by sea.cs.wisc.edu; Thu, 2 Mar 95 13:13:26 -0600; AA15233 Received: from TELNET-1.SRV.CS.CMU.EDU by cs.wisc.edu; Thu, 2 Mar 95 13:13:23 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id ai01684; 1 Mar 95 14:36:19 EST Received: from GS151.SP.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id ac01673; 1 Mar 95 14:13:02 EST Received: from GS151.SP.CS.CMU.EDU by GS151.SP.CS.CMU.EDU id aa26686; 1 Mar 95 14:11:48 EST Received: from EDRC.CMU.EDU by B.GP.CS.CMU.EDU id aa09091; 1 Mar 95 13:15:14 EST Received: from curly.cc.utexas.edu by EDRC.CMU.EDU id aa19448; 1 Mar 95 13:14:24 EST Received: (from ajit@localhost) by curly.cc.utexas.edu (8.6.8.1/8.6.6/cc-uts-1.7) id MAA18317; Wed, 1 Mar 1995 12:14:20 -0600 Date: Wed, 1 Mar 1995 12:14:20 -0600 From: Ajit Dingankar <ajit@uts.cc.utexas.edu> Message-Id: <199503011814.MAA18317@curly.cc.utexas.edu> To: Connectionists@cs.cmu.edu Subject: On Approximation of Linear Functionals on L_p Spaces Reply-To: ajit@uts.cc.utexas.edu Organization: The University of Texas at Austin Ftp-Host: archive.cis.ohio-state.edu Ftp-Filename: /pub/neuroprose/dingankar.linear-functionals.ps.Z **DO NOT FORWARD TO OTHER GROUPS** Sorry, no hardcopies available. URL: ftp://archive.cis.ohio-state.edu/pub/neuroprose/dingankar.linear-functionals.ps.Z BiBTeX entry: @ARTICLE{atd16, AUTHOR = "Sandberg, I. W. and Dingankar, A. T.", TITLE = "{On Approximation of Linear Functionals on $L_p$ Spaces}", JOURNAL = "IEEE Transactions on Circuits and Systems-I: Fundamental Theory and Applications", VOLUME = {}, NUMBER = {}, PAGES = {}, YEAR = "1995", } On Approximation of Linear Functionals on L_p Spaces ---------------------------------------------------- ABSTRACT In a recent paper certain approximations to continuous nonlinear functionals defined on an $L_p$ space $ (1 < p < \infty) $ are shown to exist. These approximations may be realized by sigmoidal neural networks employing a linear input layer that implements finite sums of integrals of a certain type. In another recent paper similar approximation results are obtained using elements of a general class of continuous linear functionals. In this note we describe a connection between these results by showing that every continuous linear functional on a compact subset of $L_p$ may be approximated uniformly by certain finite sums of integrals. We also describe the relevance of this result to the approximation of continuous nonlinear functionals with neural networks. From mas@isca.pdial.interpath.net Thu Mar 2 13:13:32 1995 Received: from cs.wisc.edu by sea.cs.wisc.edu; Thu, 2 Mar 95 13:13:28 -0600; AA15239 Message-Id: <9503021913.AA13804@cs.wisc.edu> Received: from TELNET-1.SRV.CS.CMU.EDU by cs.wisc.edu; Thu, 2 Mar 95 13:13:25 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aj01684; 1 Mar 95 14:36:48 EST Received: from GS151.SP.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id ad01673; 1 Mar 95 14:13:04 EST Received: from GS151.SP.CS.CMU.EDU by GS151.SP.CS.CMU.EDU id aa26689; 1 Mar 95 14:12:21 EST Date: Wed, 1 Mar 1995 12:52:38 -0500 X-Sender: isca@mail-hub.interpath.net X-Mailer: Windows Eudora Version 1.4.3 Mime-Version: 1.0 Content-Type: multipart/mixed; boundary="=====================_794087606==_" To: goel@mtu.edu From: Mary Ann Sullivan <mas@isca.pdial.interpath.net> Subject: CALL FOR PAPERS: ISCA INT'L CONF ON COMPUTER APPLICATIONS IN INDUSTRY & ENGINEERING Nov. 29 - Dec. 1, 1995 Honolulu, Hawaii X-Attachments: C:\EUDORA\HAWAII-C.TXT; CALL FOR PAPERS International Conference on Computer Applications in Industry and Engineering November 29 - December 1, 1995 Sheraton Princess Kaiulani Hotel Honolulu, Hawaii USA Sponsored by the International Society for Computers and Their Applications (ISCA) CONFERENCE CHAIR PROGRAM CHAIR M. Sami Fadali Ashok Goel University of Nevada, Reno Michigan Technological Univ. Tel: (702) 784-6951 Tel: (906) 487-2868 Fax: (702) 784-6627 PROGRAM COMMITTEE N. Alexandridis, George Wash. U. R. Ammar, U. of Connecticut S. Busovaca, Calif. State U. M. Cohen, U. of California B. Dahanayake, McMaster U. S. P. Dandamudi, Carleton U. R. E. Gantenbein, U. of Wyoming I. Ghansah, Calif. State U. D. L. Hudson, U. of California H. Jiang, U. of Nebraska J. Kim, Bellcore G. Lee, North Carolina State U. S. J. Lee, Yuan-Ze Inst. of Techn. Z. H. Luo, Nagaoka U. M. Owrang, American U. W. Perrizo, North Dakota St. U. D. Pheanis, Arizona State U. H. A. Sholl, U. of Connecticut R. Weiss, Inst. Tech. Informatik X. Wu, Monash U. Theme: Computer Applications for the 1990's and Beyond The International Conference on Computer Applications in Industry and Engineering will feature contributed as well as invited papers. The topics will include, but are not limited to, the following: Algorithm development Automation systems Computer modeling Intelligent systems Computer simulation Signal processing systems Software Development VLSI Multimedia applications Control systems Computer-aided design/manufacturing Transportation systems Computer-aided education Electrical circuits & systems Computer architecture Chemical engineering systems Computer networks Energy systems. Neural Networks Biomedical systems Environmental systems Instructions to Authors: Three copies of an extended summary (limited to 4 pages including figures and references) or of the full paper (not to exceed 15 pages), including title, author(s) name, affiliation, mailing address, telephone, fax and e-mail (if any) of the principal author/intended speaker should reach the Program Chair on or before the deadline date of April 1 at the following address: Dr. Ashok K. Goel Telephone: (906) 487-2868 Dept. of Electrical Engr. Fax: (906) 487-2949 Michigan Technological U. E-mail: goel@mtu.edu Houghton, MI 49931 SPECIAL SESSIONS: Proposals for organizing Special Sessions on the theme of the conference are also invited. These should reach the Program Chair at the above address before March 1. Authors wishing to have their papers reviewed for possible publication in the ISCA International Journal of Computers and Their Applications should send four copies of expanded versions of their paper directly to the Editor, Professor Howard Sholl, University of Connecticut, U-31, 233 Glenbrook Road, Storrs, CT 06269-4051. The Editor also welcomes papers not submitted to the ISCA conference. IMPORTANT DATES Summary/Full Paper Submission Deadline: April 1, 1995 Notification of Acceptance: June 1, 1995 Preregistration & Camera-ready Paper Due: September 1, 1995 Ms. Mary Ann Sullivan International Society for Computers Phone: (919) 847-3747 and Their Applications (ISCA) Fax: (919) 676-0666 Headquarters Office E-mail: mas@isca.pdial.interpath.net 8820 Six Forks Road Raleigh, NC 27615-2969 From esann@dice.ucl.ac.be Thu Mar 2 13:13:34 1995 Received: from cs.wisc.edu by sea.cs.wisc.edu; Thu, 2 Mar 95 13:13:23 -0600; AA15231 Received: from TELNET-1.SRV.CS.CMU.EDU by cs.wisc.edu; Thu, 2 Mar 95 13:13:19 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id ag01684; 1 Mar 95 14:34:41 EST Received: from GS151.SP.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa01673; 1 Mar 95 14:12:55 EST Received: from GS151.SP.CS.CMU.EDU by GS151.SP.CS.CMU.EDU id aa26680; 1 Mar 95 14:11:09 EST Received: from EDRC.CMU.EDU by B.GP.CS.CMU.EDU id aa08216; 1 Mar 95 12:15:49 EST Received: from ns1.dice.ucl.ac.be by EDRC.CMU.EDU id aa19154; 1 Mar 95 12:14:50 EST Received: from [130.104.31.81] by ns1.dice.ucl.ac.be (mp-14/10/92/SMI-4.1) id SAA03612; Wed, 1 Mar 1995 18:15:47 +0100 Message-Id: <199503011715.SAA03612@ns1.dice.ucl.ac.be> X-Sender: esann@ns1.dice.ucl.ac.be. Mime-Version: 1.0 Content-Type: text/plain; charset="us-ascii" Date: Wed, 1 Mar 1995 18:18:49 +0200 To: NEURO1-L@UICVM.CC.UIC.EDU, neuron-request@CATTELL.psych.upenn.edu, Connectionists@cs.cmu.edu, enns-list@dcs.kcl.ac.uk, neur-sci@dl.ac.uk, comp-neuro@smaug.bbb.caltech.edu, frog-net@rana.usc.edu, echos@dmi.ens.fr, cogni-info@univ-lyon1.fr From: esann@dice.ucl.ac.be Subject: Neural Processing Letters: abstracts on WWW ------------------------- Neural Processing Letters Abstracts on WWW server ------------------------- According to the large number of requests that we received, all abstracts of papers in published issues of Neural Processing Letters are now available on the WWW and FTP servers of the journal. You may connect to these servers at the following addresses: - FTP server: ftp.dice.ucl.ac.be directory: /pub/neural-nets/NPL - WWW server: http://www.dice.ucl.ac.be/neural-nets/NPL/NPL.html Subscription to the journal is also now possible by credit card. If you have no access to these servers, or for any other information (subscriptions, instructions for authors, free sample copies,...), please don't hesitate to contact directly the publisher: D facto publications 45 rue Masui B-1210 Brussels Belgium Phone: + 32 2 245 43 63 Fax: + 32 2 245 46 94 _____________________________ D facto publications - conference services 45 rue Masui 1210 Brussels Belgium tel: +32 2 245 43 63 fax: +32 2 245 46 94 _____________________________ From wahba@stat.wisc.edu Thu Mar 2 13:13:34 1995 Received: from cs.wisc.edu by sea.cs.wisc.edu; Thu, 2 Mar 95 13:13:31 -0600; AA15248 Received: from TELNET-1.SRV.CS.CMU.EDU by cs.wisc.edu; Thu, 2 Mar 95 13:13:29 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id ak01684; 1 Mar 95 14:37:29 EST Received: from GS151.SP.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa01675; 1 Mar 95 14:13:57 EST Received: from GS151.SP.CS.CMU.EDU by GS151.SP.CS.CMU.EDU id aa26693; 1 Mar 95 14:13:01 EST Received: from EDRC.CMU.EDU by B.GP.CS.CMU.EDU id aa29004; 28 Feb 95 21:18:08 EST Received: from hera.stat.wisc.edu by EDRC.CMU.EDU id aa15714; 28 Feb 95 21:17:27 EST Date: Tue, 28 Feb 95 20:17:22 -0600 From: Grace Wahba <wahba@stat.wisc.edu> Message-Id: <9503010217.AA18322@hera.stat.wisc.edu> Received: by hera.stat.wisc.edu; Tue, 28 Feb 95 20:17:22 -0600 To: connectionists@cs.cmu.edu Subject: SS-ANOVA for `soft classification' Cc: chong@pop.stat.purdue.edu, wahba@stat.wisc.edu, yuedong@sph.umich.edu Announcing: Smoothing Spline ANOVA for Exponential Families, with Application to the Wisconsin Epidemiological Study of Retinopathy. by Grace Wahba, Yuedong Wang, Chong Gu, Ronald Klein, MD and Barbara Klein, MD. UWisconsin- Madison Statistics Dept TR 940, Dec. 1994 (WWGKK) ftp: ftp.stat.wisc.edu/pub/wahba/exptl.ssanova.ps.gz Mosaic: http://www.stat.wisc.edu/~wahba/wahba.html - then click on ftp ...... GRKPACK: Fitting Smoothing Spline ANOVA Models for Exponential Families. by Yuedong Wang. UWisconsin- Madison Statistics Dept TR 942, Jan. 1995. (GRKPACK-doc) ftp: ftp.stat.wisc.edu/pub/wahba/grkpack.ps.gz Mosaic: http://www.stat.wisc.edu/~wahba/wahba.html - then click on ftp ....... In WWGKK we develop Smoothing Spline ANOVA (SS-ANOVA) models for estimating the probability that an instance (subject) will be in class 1 as opposed to class 0, given a vector of predictor variables t (`soft' classification). We observe {y_i, t(i), i = 1,..,n} where y_i is 1 or 0 according as subject i's response is `success' or `failure', and t(i) is a vector of predictor variables for the i-th subject. Letting p(t) be the probability that a subject whose predictor variables are t, has a `success' response, we estimate p(t) = exp{f(t)}/(1 + exp{f(t)}} from this data using a smoothing spline ANOVA representation of f. An ANOVA representation gives f as a sum of functions of one variable (main effects) plus sums of functions of two variables (two -factor interactions) ...etc. This representation provides an interpretable alternative to a neural net. The following issues are addressed in this paper; (1) Methods for deciding which terms in the ANOVA decomposition to include (model selection), (2) Methods for choosing good values of the regularization (smoothing) parameters, which control the bias-variance tradeoff, (3) Methods for making confidence statements concerning the estimate, (4) Numerical algorithms for the calculations, and, finally, (5) Public software (GRKPACK). The overall scheme is applied to data from the Wisconsin Epidemiologic Study of Diabetic Retinopathy (WESDR) to model the risk of progression of diabetic retinopathy {`success'} as a function of glycosylated hemoglobin, duration of diabetes and body mass index {t}. Cross sectional plots provide interpretable information about these risk factors. This paper provided the basis for Grace Wahba's Neyman Lecture. A preliminary version appeared in NIPS-6. GRKPACK-doc provides documentation for the code GRKPACK, which implements (2)-(4) above. The code for GRKPACK is available in netlib in the file gcv/grkpack.shar. It is recommended that it be retrieved via Mosaic: http://www.netlib.org goto The Netlib Repository, goto gcv, rather than via the robot mailserver, which may subdivide the file. Included in GRKPACK are several examples including the analysis described in WWGKK and the WESDR data. Comments and suggestions concerning the code are requested to be sent to Yuedong Wang yuedong@umich.edu. From john@dcs.rhbnc.ac.uk Thu Mar 2 13:15:09 1995 Received: from cs.wisc.edu by sea.cs.wisc.edu; Thu, 2 Mar 95 13:12:54 -0600; AA15198 Received: from TELNET-1.SRV.CS.CMU.EDU by cs.wisc.edu; Thu, 2 Mar 95 13:12:50 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa01684; 1 Mar 95 14:30:27 EST Received: from GS151.SP.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id ab01663; 1 Mar 95 14:07:29 EST Received: from GS151.SP.CS.CMU.EDU by GS151.SP.CS.CMU.EDU id aa26648; 1 Mar 95 14:06:31 EST Received: from EDRC.CMU.EDU by B.GP.CS.CMU.EDU id aa26538; 28 Feb 95 17:49:01 EST Received: from platon.cs.rhbnc.ac.uk by EDRC.CMU.EDU id aa14848; 28 Feb 95 17:46:06 EST Received: from localhost (localhost [127.0.0.1]) by platon.cs.rhbnc.ac.uk (8.6.9/8.6.9) with SMTP id WAA03485 ; Tue, 28 Feb 1995 22:43:37 GMT From: John Shawe-Taylor <john@dcs.rhbnc.ac.uk> Message-Id: <199502282243.WAA03485@platon.cs.rhbnc.ac.uk> X-Authentication-Warning: platon.cs.rhbnc.ac.uk: Host localhost didn't use HELO protocol To: john@dcs.rhbnc.ac.uk, alex@dcs.rhbnc.ac.uk, pete@dcs.rhbnc.ac.uk, dave@dcs.rhbnc.ac.uk, anthony@vax.lse.ac.uk, Paul.Vitanyi@cwi.nl, Esko Ukkonen <Esko.Ukkonen@cs.Helsinki.FI>, orponen@igi.tu-graz.ac.at, Michel.Cosnard@lip.ens-lyon.fr, maass@igi.tu-graz.ac.at, cesabian@ghost.dsi.unimi.it, mauri <gmauri@ghost.dsi.unimi.it>, Felipe Cucker <cucker@upf.es>, smichaux@vm1.umh.ac.be, sbruyere@vm1.umh.ac.be, chrmich@SUN1.UMH.AC.BE, sboffa@vm1.umh.ac.be, meer@rwth-aachen.de, gavalda@lsi.upc.es, balqui@lsi.upc.es, torras@ic.upc.es, bruf@igi.tu-graz.ac.at, jpd@pip.fpms.ac.be, ferretti@imiucca.csi.unimi.it, grb10@phx.cam.ac.uk, hpaugam@lip.ens-lyon.fr, mschmitt@igi.tu-graz.ac.at, boldi@ghost.dsi.unimi.it, colt@cs.uiuc.edu, Connectionists@cs.cmu.edu, neuron-request@cattell.psych.upenn.edu Subject: Technical Report Series in Neural and Computational Learning Date: Tue, 28 Feb 95 22:43:37 +0000 X-Mts: smtp The European Community ESPRIT Working Group in Neural and Computational Learning Theory (NeuroCOLT): three new reports available ---------------------------------------- NeuroCOLT Technical Report NC-TR-95-015: ---------------------------------------- Computability and complexity over the reals by Paolo Boldi, University of Milan Abstract: In this work, we sketch a (rather superficial) survey about the problem of extending some of the classical notions from computation and complexity theory to the non-classical realm of real numbers. We first present an algorithmic approach, deeply studied by Blum, Shub, Smale et al., and give a non-trivial separation result recently obtained by Cucker. Then, we introduce some concepts from another line of research, namely the one based on the notion of computable real number. ---------------------------------------- NeuroCOLT Technical Report NC-TR-95-016: ---------------------------------------- Probably Approximately Optimal Satisficing Strategies by Russell Greiner, Siemens Corporate Research Pekka Orponen, Department of Computer Science, University of Helsinki Abstract: A {\em satisficing search problem} consists of a set of probabilistic experiments to be performed in some order, seeking a satisfying configuration of successes and failures. The expected cost of the search depends both on the success probabilities of the individual experiments, and on the {\em search strategy}, which specifies the order in which the experiments are to be performed. A strategy that minimizes the expected cost is {\em optimal}. Earlier work has provided ``optimizing functions'' that compute optimal strategies for certain classes of search problems from the success probabilities of the individual experiments. We extend those results by providing a general model of such strategies, and an algorithm \pao\ that identifies an approximately optimal strategy when the probability values are not known. The algorithm first estimates the relevant probabilities from a number of trials of each undetermined experiment, and then uses these estimates, and the proper optimizing function, to identify a strategy whose cost is, with high probability, close to optimal. We also show that if the search problem can be formulated as an and-or tree, then the PAO algorithm can also ``learn while doing'', i.e. gather the necessary statistics while performing the search. ---------------------------------------- NeuroCOLT Technical Report NC-TR-95-018: ---------------------------------------- On real Turing machines that toss coins by Felipe Cucker, Universitat Pompeu Fabra, Marek Karpinski, Universit\"at Bonn, Pascal Koiran, DIMACS, Rutgers University, Thomas Lickteig, Universit\"at Bonn, Kai Werther, Universit\"at Bonn Abstract: In this paper we consider real counterparts of classical probabilistic complexity classes in the framework of real Turing machines as introduced by Blum, Shub, and Smale \cite{BSS}. We give an extension of the well-known ``$\BPP \subseteq \P/\poly$'' result from discrete complexity theory to a very general setting in the real number model. This result holds for real inputs, real outputs, and random elements drawn from an arbitrary probability distribution over~$\R^m$. Then we turn to the study of Boolean parts, that is, classes of languages of zero-one vectors accepted by real machines. In particular we show that the classes $\BPP$, $\PP$, $\PH$, and $\PSPACE$ are not enlarged by allowing the use of real constants and arithmetic at unit cost provided we restrict branching to equality tests. ----------------------- The Report NC-TR-95-015 can be accessed and printed as follows % ftp cscx.cs.rhbnc.ac.uk (134.219.200.45) Name: anonymous password: your full email address ftp> cd pub/neurocolt/tech_reports ftp> binary ftp> get nc-tr-95-015.ps.Z ftp> bye % zcat nc-tr-95-015.ps.Z | lpr -l Similarly for the other technical report. Uncompressed versions of the postscript files have also been left for anyone not having an uncompress facility. A full list of the currently available Technical Reports in the Series is held in a file `abstracts' in the same directory. The files may also be accessed via WWW starting from the NeuroCOLT homepage: http://www.dcs.rhbnc.ac.uk/neurocolt.html Best wishes John Shawe-Taylor From ajit@uts.cc.utexas.edu Thu Mar 2 23:33:16 1995 Received: from cs.wisc.edu by sea.cs.wisc.edu; Thu, 2 Mar 95 23:33:13 -0600; AA20616 Received: from TELNET-1.SRV.CS.CMU.EDU by cs.wisc.edu; Thu, 2 Mar 95 23:33:11 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id ah01684; 1 Mar 95 14:35:49 EST Received: from GS151.SP.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id ab01673; 1 Mar 95 14:12:59 EST Received: from GS151.SP.CS.CMU.EDU by GS151.SP.CS.CMU.EDU id aa26683; 1 Mar 95 14:11:41 EST Received: from RI.CMU.EDU by B.GP.CS.CMU.EDU id aa08910; 1 Mar 95 13:06:21 EST Received: from curly.cc.utexas.edu by RI.CMU.EDU id aa26888; 1 Mar 95 13:05:51 EST Received: (from ajit@localhost) by curly.cc.utexas.edu (8.6.8.1/8.6.6/cc-uts-1.7) id MAA30724; Wed, 1 Mar 1995 12:05:47 -0600 Date: Wed, 1 Mar 1995 12:05:47 -0600 From: Ajit Dingankar <ajit@uts.cc.utexas.edu> Message-Id: <199503011805.MAA30724@curly.cc.utexas.edu> To: Connectionists@cs.cmu.edu Subject: A Note on Error Bounds for Approximation in Inner Product Spaces Reply-To: ajit@uts.cc.utexas.edu Organization: The University of Texas at Austin Ftp-Host: archive.cis.ohio-state.edu Ftp-Filename: /pub/neuroprose/dingankar.error-bounds.ps.Z **DO NOT FORWARD TO OTHER GROUPS** Sorry, no hardcopies available. URL: ftp://archive.cis.ohio-state.edu/pub/neuroprose/dingankar.error-bounds.ps.Z BiBTeX entry: @ARTICLE{atd15, AUTHOR = "Dingankar, A. T. and Sandberg, I. W.", TITLE = "{A Note on Error Bounds for Approximation in Inner Product Spaces}", JOURNAL = "Circuits, Systems and Signal Processing", VOLUME = {}, NUMBER = {}, PAGES = {}, YEAR = {1996}, } A Note on Error Bounds for Approximation in Inner Product Spaces ---------------------------------------------------------------- ABSTRACT In a recent paper a method is described for constructing certain approximations to a general element in the closure of the convex hull of a subset of an inner product space. This is of interest in connection with neural networks. Here we give an algorithm that generates simpler approximants with somewhat less computational cost. From thodberg@nn.dmri.dk Fri Mar 3 18:56:00 1995 Received: from cs.wisc.edu by sea.cs.wisc.edu; Fri, 3 Mar 95 18:55:57 -0600; AA26583 Received: from TELNET-1.SRV.CS.CMU.EDU by cs.wisc.edu; Fri, 3 Mar 95 18:55:49 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa04047; 2 Mar 95 12:50:23 EST Received: from GS151.SP.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa04044; 2 Mar 95 12:36:51 EST Received: from GS151.SP.CS.CMU.EDU by GS151.SP.CS.CMU.EDU id aa28205; 2 Mar 95 12:36:09 EST Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa09865; 1 Mar 95 14:05:43 EST Received: from danpost.uni-c.dk by CS.CMU.EDU id aa11893; 1 Mar 95 14:04:48 EST Received: from dmri.dk ([130.227.75.3]) by danpost.uni-c.dk (8.6.4/8.6) with SMTP id UAA18620 for <Connectionists@cs.cmu.edu>; Wed, 1 Mar 1995 20:03:55 +0100 Received: by dmri.dk (5.x/SMI-SVR4) id AA02531; Wed, 1 Mar 1995 20:02:22 +0100 Date: Wed, 1 Mar 1995 20:02:22 +0100 From: Hans Henrik Thodberg <thodberg@nn.dmri.dk> Message-Id: <9503011902.AA02531@dmri.dk> To: Connectionists@cs.cmu.edu Subject: TR: Ace-of-Bayes with ARD X-Sun-Charset: US-ASCII The following 33 pages long manuscript is now available by ftp: FTP-host: archive.cis.ohio-state.edu FTP-filename: /pub/neuroprose/thodberg.bayes-ard.ps.Z or URL (WWW): ftp://archive.cis.ohio-state.edu/pub/neuroprose/thodberg.bayes-ard.ps.Z Hardcopies are not avaliable. ---------------------------------------------------------------------------- A Review of Bayesian Neural Networks with an Application to Near Infrared Spectroscopy. Hans Henrik Thodberg The Danish Meat Research Institute Abstract MacKay's Bayesian framework for backpropagation is a practical and powerful means to improve the generalisation ability of neural networks. It is based on a Gaussian approximation to the posterior weight distribution. The framework is extended, reviewed and demonstrated in a pedagogical way. The notation is simplified using the ordinary weight decay parameter, and a detailed and explicit procedure for adjusting several weight decay parameters is given. Bayesian backprop is applied in the prediction of fat content in minced meat from near infrared spectra. It outperforms ``early stopping'' as well as quadratic regression. The evidence of a committee of differently trained networks is computed, and the corresponding improved generalisation is verified. The error bars on the predictions of the fat content are computed. There are three contributors: The random noise, the uncertainty in the weights, and the deviation among the committee members. The Bayesian framework is compared to Moody's GPE. Finally, MacKay and Neal's Automatic Relevance Determination, in which the weight decay parameters depend on the input number, is applied to the data with improved results. ---------------------------------------------------------------------------- The manuscript is a revised version of thodberg.ace-of-bayes.ps.Z which is also in neuroprose. The main changes are the following: Pruning has been taken out (it is treated in a separate paper), the treatment of committees is extended, and there is a new section demonstrating the powerful Automatic Relevance Determination. The data used in the paper are now available by ftp. The paper is submitted to IEEE Trans. on Neural Networks. Comments are welcome! ---------------------------------------------------------------------------- Hans Henrik Thodberg Email(NEW!!): thodberg@nn.dmri.dk Danish Meat Research Institute Phone: (+45) 42 36 12 00 Maglegaardsvej 2, Postboks 57 Fax: (+45) 42 36 48 36 DK-4000 Roskilde, Denmark ---------------------------------------------------------------------------- From Volker.Tresp@zfe.siemens.de Fri Mar 3 18:56:04 1995 Received: from cs.wisc.edu by sea.cs.wisc.edu; Fri, 3 Mar 95 18:55:59 -0600; AA26589 Received: from TELNET-1.SRV.CS.CMU.EDU by cs.wisc.edu; Fri, 3 Mar 95 18:55:57 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id ab04047; 2 Mar 95 12:51:14 EST Received: from GS151.SP.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id ab04044; 2 Mar 95 12:36:58 EST Received: from GS151.SP.CS.CMU.EDU by GS151.SP.CS.CMU.EDU id aa28208; 2 Mar 95 12:36:26 EST Received: from RI.CMU.EDU by B.GP.CS.CMU.EDU id aa11211; 1 Mar 95 15:07:30 EST Received: from david.zfe.siemens.de by RI.CMU.EDU id aa27357; 1 Mar 95 15:06:29 EST Received: from ztivax.zfe.siemens.de by david.zfe.siemens.de with SMTP id AA28601 (5.67a/IDA-1.5 for <Connectionists@cs.cmu.edu>); Wed, 1 Mar 1995 21:06:17 +0100 Received: from train.zfe.siemens.de (train) by ztivax.zfe.siemens.de with SMTP id AA18097 (5.67a/IDA-1.5 for <Connectionists@CS.CMU.EDU>); Wed, 1 Mar 1995 21:06:19 +0100 Received: from marmor.zfe.siemens.de (marmor) by train.zfe.siemens.de with SMTP id AA11490 (5.67a/IDA-1.5 for <Connectionists@CS.CMU.EDU>); Wed, 1 Mar 1995 21:06:21 +0100 Date: Wed, 1 Mar 1995 21:06:21 +0100 From: Volker Tresp <Volker.Tresp@zfe.siemens.de> Message-Id: <199503012006.AA11490@train.zfe.siemens.de> To: Connectionists@cs.cmu.edu Subject: 2 Papers available on combining estimators and missing data The -2- files tresp.combining.ps.Z and tresp.effic_miss.ps.Z can now be copied from Neuroprose. The papers are 8 and 9 pages long. Hardcopies copies are not available. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% FTP-host: archive.cis.ohio-state.edu FTP-filename: /pub/neuroprose/tresp.combining.ps.Z COMBINING ESTIMATORS USING NON-CONSTANT WEIGHTING FUNCTIONS by Volker Tresp and Michiaki Taniguchi Abstract: This paper discusses the linearly weighted combination of estimators in which the weighting functions are dependent on the input. We show that the weighting functions can be derived either by evaluating the input dependent variance of each estimator or by estimating how likely it is that a given estimator has seen data in the region of the input space close to the input pattern. The latter solution is closely related to the mixture of experts approach and we show how learning rules for the mixture of experts can be derived from the theory about learning with missing features. The presented approaches are modular since the weighting functions can easily be modified (no retraining) if more estimators are added. Furthermore, it is easy to incorporate estimators which were not derived from data such as expert systems or algorithms. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% FTP-host: archive.cis.ohio-state.edu FTP-filename: /pub/neuroprose/tresp.effic_miss.ps.Z EFFICIENT METHODS FOR DEALING WITH MISSING DATA IN SUPERVISED LEARNING by Volker Tresp, Ralph Neuneier, and Subutai Ahmad Abstract: We present efficient algorithms for dealing with the problem of missing inputs (incomplete feature vectors) during training and recall. Our approach is based on the approximation of the input data distribution using Parzen windows. For recall, we obtain closed form solutions for arbitrary feedforward networks. For training, we show how the backpropagation step for an incomplete pattern can be approximated by a weighted averaged backpropagation step. The complexity of the solutions for training and recall is independent of the number of missing features. We verify our theoretical results using one classification and one regression problem. The papers will appear in G. Tesauro, D. S. Touretzky and T. K. Leen, eds., "Advances in Neural Information Processing Systems 7", MIT Press, Cambridge MA, 1995. ________________________________________ Volker Tresp Siemens AG ZFE T SN4 81730 Munich Germany email: Volker.Tresp@zfe.siemens.de Phone: +49 89 636 49408 Fax: +49 89 636 3320 ________________________________________ From delliott@src.umd.edu Fri Mar 3 18:56:05 1995 Received: from cs.wisc.edu by sea.cs.wisc.edu; Fri, 3 Mar 95 18:56:02 -0600; AA26591 Received: from TELNET-1.SRV.CS.CMU.EDU by cs.wisc.edu; Fri, 3 Mar 95 18:55:59 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id ac04047; 2 Mar 95 12:52:16 EST Received: from GS151.SP.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id ac04044; 2 Mar 95 12:37:02 EST Received: from GS151.SP.CS.CMU.EDU by GS151.SP.CS.CMU.EDU id aa28211; 2 Mar 95 12:36:38 EST Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa21999; 2 Mar 95 3:19:46 EST Received: from newra.src.umd.edu by CS.CMU.EDU id aa17913; 2 Mar 95 3:16:32 EST Received: (delliott@localhost) by newra.src.umd.edu (8.6.10/8.6.4) id DAA23586 for Connectionists@CS.CMU.edu; Thu, 2 Mar 1995 03:16:30 -0500 Date: Thu, 2 Mar 1995 03:16:30 -0500 From: "David L. Elliott" <delliott@src.umd.edu> Message-Id: <199503020816.DAA23586@newra.src.umd.edu> To: Connectionists@cs.cmu.edu Subject: NN paper (identification of systems) available by anon ftp The following paper, which has been accepted for an invited session at the 1995 American Control Conference, will be available until the conference (June 21 1995) by anonymous ftp to the ftp server for the Institute for Systems Research ftp://ftp.isr.umd.edu/pub/ISRTR/ps Filename: TR95-17.ps Title: "Reconstruction of nonlinear systems with delay lines and feedforward networks" Author: David L. Elliott, ISR, Univ. of Maryland, College Park Abstract: Nonlinear system theory ideas have led to a method for approximating the dynamics of a nonlinear system in a bounded region of its state space, by training a feedforward neural network which is then reconfigured in recursive mode to provide a stand-alone simulator of the original system. The input layer of the neural network contains time-delayed samples of one or more system outputs and control inputs. Autonomous systems can also be simulated in this way by providing impulse inputs. My apology for the 0.9M filesize-- the paper is only 5 pages, but assembling diverse PS text and figures was inefficient. Printing time is short, however. Criticisms and comments will be especially helpful if sent before June 1, and will be very welcome. David From srw1001@eng.cam.ac.uk Fri Mar 3 18:56:16 1995 Received: from cs.wisc.edu by sea.cs.wisc.edu; Fri, 3 Mar 95 18:56:13 -0600; AA26601 Received: from TELNET-1.SRV.CS.CMU.EDU by cs.wisc.edu; Fri, 3 Mar 95 18:56:01 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa04066; 2 Mar 95 13:00:47 EST Received: from GS151.SP.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa04050; 2 Mar 95 12:38:00 EST Received: from GS151.SP.CS.CMU.EDU by GS151.SP.CS.CMU.EDU id aa28215; 2 Mar 95 12:36:54 EST Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id ab27353; 2 Mar 95 8:53:22 EST Received: from spanner.eng.cam.ac.uk by CS.CMU.EDU id aa19091; 2 Mar 95 8:52:27 EST Received: from dsl.eng.cam.ac.uk (via root@dsl.eng.cam.ac.uk [129.169.24.1]) by spanner.eng.cam.ac.uk with ESMTP id NAA00638 for <Connectionists@cs.cmu.edu>; Thu, 2 Mar 1995 13:51:47 GMT Received: from fear.eng.cam.ac.uk (via srw1001@fear.eng.cam.ac.uk [129.169.24.29]) by dsl.eng.cam.ac.uk with SMTP id NAA18444 for <Connectionists@cs.cmu.edu>; Thu, 2 Mar 1995 13:51:46 GMT From: srw1001@eng.cam.ac.uk Date: Thu, 2 Mar 95 13:51:45 GMT Message-Id: <9503021351.22738@fear.eng.cam.ac.uk> Received: by fear.eng.cam.ac.uk id AA22738 for Connectionists@cs.cmu.edu; Thu, 2 Mar 95 13:51:45 GMT To: Connectionists@cs.cmu.edu Subject: Paper availble : Non-linear Prediction using Hierarchical Mixtures of Experts. The following paper is available by anonymous ftp from the archive of the Speech, Vision and Robotics Group at the Cambridge University Engineering Department and the Neuroprose archives. NON-LINEAR PREDICTION OF ACOUSTIC VECTORS USING HIERARCHICAL MIXTURES OF EXPERTS. Steve Waterhouse and Tony Robinson Cambridge University Engineering Department Trumpington Street Cambridge CB2 1PZ England Abstract In this paper we consider speech coding as a problem of speech modelling. In particular, prediction of parameterised speech over short time segments is performed using the Hierarchical Mixture of Experts (HME) \cite{JordanJacobs94}. The HME gives two advantages over traditional non-linear function approximators such as the Multi-Layer Perceptron (MLP); a statistical understanding of the operation of the predictor and provision of information about the performance of the predictor in the form of likelihood information and local error bars. These two issues are examined on both toy and real world problems of regression and time series prediction. In the speech coding context, we extend the principle of combining local predictions via the HME to a Vector Quantization scheme in which fixed local codebooks are combined on-line for each observation. To appear in Advances in Neural Information Processing Systems 7, edited by Gerald Tesauro, David Touretzky, and Todd Leen. ************************ How to obtain a copy ************************ a) via ftp from Cambridge University SVR: unix> ftp svr-ftp.eng.cam.ac.uk Name: anonymous Password: (type your email address) ftp> cd reports ftp> binary ftp> get waterhouse_nips94.ps.Z ftp> quit unix> uncompress waterhouse_nips94.ps.Z unix> lpr waterhouse_nips94.ps (or however you print PostScript) b) via ftp from neuroprose archive: unix> ftp Name: anonymous Password: (type your email address) ftp> cd pub/neuroprose/reports ftp> binary ftp> get waterhouse.nips94.ps.Z ftp> quit unix> uncompress waterhouse.nips94.ps.Z unix> lpr waterhouse.nips94.ps (or however you print PostScript) c) or email me: srw1001@eng.cam.ac.uk d) (easiest) access my WWW page http://svr-www.eng.cam.ac.uk/~srw1001, where the file is symlinked. ----------------------------------------------------- Steve Waterhouse, Information Engineering, Cambridge University Engineering Department, Trumpington Street, Cambridge CB2 1PZ, UK. Email: srw1001@eng.cam.ac.uk Phone : (0223) 332800 World Wide Web: http://svr-www.eng.cam.ac.uk/~srw1001 From srw1001@eng.cam.ac.uk Fri Mar 3 18:56:20 1995 Received: from cs.wisc.edu by sea.cs.wisc.edu; Fri, 3 Mar 95 18:56:16 -0600; AA26607 Received: from TELNET-1.SRV.CS.CMU.EDU by cs.wisc.edu; Fri, 3 Mar 95 18:56:12 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id ab04066; 2 Mar 95 13:02:01 EST Received: from GS151.SP.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id ab04050; 2 Mar 95 12:38:01 EST Received: from GS151.SP.CS.CMU.EDU by GS151.SP.CS.CMU.EDU id aa28219; 2 Mar 95 12:37:06 EST Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa27388; 2 Mar 95 8:54:23 EST Received: from spanner.eng.cam.ac.uk by CS.CMU.EDU id aa19099; 2 Mar 95 8:52:51 EST Received: from dsl.eng.cam.ac.uk (via root@dsl.eng.cam.ac.uk [129.169.24.1]) by spanner.eng.cam.ac.uk with ESMTP id NAA00690 for <Connectionists@cs.cmu.edu>; Thu, 2 Mar 1995 13:52:41 GMT Received: from fear.eng.cam.ac.uk (via srw1001@fear.eng.cam.ac.uk [129.169.24.29]) by dsl.eng.cam.ac.uk with SMTP id NAA18457 for <Connectionists@cs.cmu.edu>; Thu, 2 Mar 1995 13:52:40 GMT From: srw1001@eng.cam.ac.uk Date: Thu, 2 Mar 95 13:52:39 GMT Message-Id: <9503021352.22748@fear.eng.cam.ac.uk> Received: by fear.eng.cam.ac.uk id AA22748 for Connectionists@cs.cmu.edu; Thu, 2 Mar 95 13:52:39 GMT To: Connectionists@cs.cmu.edu Subject: Paper availble : Classification using Hierarchical Mixtures of Experts. The following paper is available by anonymous ftp from the archive of the Speech, Vision and Robotics Group at the Cambridge University Engineering Department and the Neuroprose archives. CLASSIFICATION USING HIERARCHICAL MIXTURES OF EXPERTS Steve Waterhouse and Tony Robinson Cambridge University Engineering Department Trumpington Street Cambridge CB2 1PZ England Abstract There has recently been widespread interest in the use of multiple models for classification and regression in the statistics and neural networks communities. The Hierarchical Mixture of Experts (HME) \cite{JordanJacobs94} has been successful in a number of regression problems, yielding significantly faster training through the use of the Expectation Maximisation algorithm. In this paper we extend the HME to classification and results are reported for three common classification benchmark tests: Exclusive-Or, N-input Parity and Two Spirals. Reference : In Proc. 1994 IEEE Workshop on Neural Networks for Signal Processing, pp 177-186. ************************ How to obtain a copy ************************ a) via ftp from Cambridge University SVR: unix> ftp svr-ftp.eng.cam.ac.uk Name: anonymous Password: (type your email address) ftp> cd reports ftp> binary ftp> get waterhouse_hme.ps.Z ftp> quit unix> uncompress waterhouse_hme.ps.Z unix> lpr waterhouse_hme.ps (or however you print PostScript) b) via ftp from neuroprose archive: unix> ftp Name: anonymous Password: (type your email address) ftp> cd pub/neuroprose/reports ftp> binary ftp> get waterhouse.hme_classification.ps.Z ftp> quit unix> uncompress waterhouse.hme_classification.ps.Z unix> lpr waterhouse.hme_classification.ps (or however you print PostScript) c) or email me: srw1001@eng.cam.ac.uk d) (easiest) access my WWW page http://svr-www.eng.cam.ac.uk/~srw1001, where the file is symlinked. ----------------------------------------------------- Steve Waterhouse, Information Engineering, Cambridge University Engineering Department, Trumpington Street, Cambridge CB2 1PZ, UK. Email: srw1001@eng.cam.ac.uk Phone : (0223) 332800 World Wide Web: http://svr-www.eng.cam.ac.uk/~srw1001 From Francoise.Fogelman@laforia.ibp.fr Fri Mar 3 18:56:23 1995 Received: from cs.wisc.edu by sea.cs.wisc.edu; Fri, 3 Mar 95 18:56:20 -0600; AA26613 Received: from TELNET-1.SRV.CS.CMU.EDU by cs.wisc.edu; Fri, 3 Mar 95 18:56:16 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa04110; 2 Mar 95 13:09:25 EST Received: from GS151.SP.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa04074; 2 Mar 95 12:54:03 EST Received: from GS151.SP.CS.CMU.EDU by GS151.SP.CS.CMU.EDU id aa28248; 2 Mar 95 12:41:54 EST Received: from EDRC.CMU.EDU by B.GP.CS.CMU.EDU id aa22850; 2 Mar 95 4:08:02 EST Received: from ibp.ibp.fr by EDRC.CMU.EDU id aa23033; 2 Mar 95 4:07:08 EST Received: from laforia.ibp.fr (laforia.ibp.fr [132.227.60.10]) by ibp.ibp.fr (8.6.10/jtpda-5.0) with ESMTP id KAA22656 for <Connectionists@cs.cmu.edu>; Thu, 2 Mar 1995 10:06:04 +0100 Received: from erato.ibp.fr (bud.ibp.fr [132.227.82.50]) by laforia.ibp.fr (8.6.10/jtpda-5.0) with ESMTP id KAA15724 for <Connectionists@cs.cmu.edu>; Thu, 2 Mar 1995 10:06:02 +0100 From: FOGELMAN Francoise + 33 1 41 28 41 70 <Francoise.Fogelman@laforia.ibp.fr> Received: from (fogelman@localhost) by erato.ibp.fr (8.6.10/jtpda-5.0) id KAA20561 for Connectionists@cs.cmu.edu; Thu, 2 Mar 1995 10:06:01 +0100 Date: Thu, 2 Mar 1995 10:06:01 +0100 Message-Id: <199503020906.KAA20561@erato.ibp.fr> To: Connectionists@cs.cmu.edu Subject: ICANN'95 *************************************************************************** UPDATED BROCHURE *************************************************************************** ***************************************************************************** XXX XXXX X XX XX XX XX XX XXXXX XXXXXX X X X X XXX XX XXX XX XX X XX X X X XXXXX XX X XX XX X XX XXXXX XXXXX X X X X XX XXX XX XXX XX XXX XXX XXXX X X XX XX XX XX XXXX XXXXX PARIS, OCTOBER 9-13, 1995 Maison de la Chimie NEURAL NETWORKS AND THEIR APPLICATIONS ***************************************************************************** SCIENTIFIC CONFERENCE INDUSTRIAL CONFERENCE TUTORIALS & EXHIBITION organized by EUROPEAN NEURAL NETWORK SOCIETY ***************************************************************************** INFORMATION ***************************************************************************** Over the last four years, the ENNS - European Neural Network Society - has held its annual conference ICANN in Helsinki (1991), Brighton (1992), Amsterdam (1993) and Sorrento (1994). This conference has become the foremost meeting for the European neural network scientific community. In 1995, ENNS will hold the ICANN meeting in Paris. The format of this conference will include a scientific conference, an industrial conference, tutorials, industrial forums and an industrial exhibition. Our challenge, in organizing this conference, is to achieve the highest scientific quality for papers presented at the scientific conference (through a strict selection procedure), together with the most convincing set of applications presented at the industrial conference (only operational, top-level applications will be considered). Papers should stress the rationale of the Neural Network approach and provide a comparison with other techniques. We thus hope to demonstrate that Neural Networks are indeed a very deep and exciting field of research, as well as a most efficient, profitable technique for the industry. To achieve these goals, we seek contributions from all the scientists, both from academy and industry, who share our interests and our quality requirements. ***************************************************************************** CALL FOR PAPERS The conference will cover the following domains : SCIENTIFIC CONFERENCE * theory * algorithms & architectures * implementations (hardware & software) * cognitive sciences & AI * neurobiology * applications identification & control image processing & vision OCR speech & signal processing prediction optimization INDUSTRIAL CONFERENCE This conference will cover two main categories: on the one hand, descriptions of tools and methods and their use in real-life cases and, on the other, descriptions of concrete applications in industry and the sector of services. All fields of application are eligible. Special sessions will be organized on specific areas of industry such as: * banking, finance & insurance * telecommunications * teledetection * process engineering, control and monitoring * oil industry * power industry * food processing * transportation * robotics * speech processing * document processing, OCR, text retrieval & indexing * VLSI & dedicated hardware * forecasting & marketing * technical diagnosis * non destructive testing * medicine * defense LOCATION The conference will be held in la Maison de la Chimie, right in the center of Paris, near les Invalides. Built in 1707, for Frederic-Maurice de la Tour, Comte d'Auvergne, Lieutenant General to King Louis XIV, the Mansion has today become a Congress Center equipped with all the modern facilities. INSTRUCTIONS TO AUTHORS Length of papers: not exceeding 6 pages in A4 format (i. e. about 8,000 characters). An electronic format will be made available at : ftp lix.polytechnique.fr login: anonymous password : your e-mail address in the directory /pub/ICANN95/out, read file README for instructions. If you want to leave messages or enquiries, you can also use : in the directory /pub/ICANN95/in, read file README for instructions. Seven copies of the papers should reach the Conference Secretariat at the address below by ****** APRIL 15 1995 ***** : ICANN'95 1 avenue Newton bp 207 92 142 CLAMART Cedex France Fax: +33 - 1 - 41 28 45 84 Submitted papers should be accompanied by a cover page giving: * the title of the paper and the author(s) name(s), * the author's address, phone number and extension, fax number and, if possible, e-mail address, * a 10-line abstract together with a list of key-words, * an indication of which conference the paper should be included in: scientific or industrial LANGUAGE Papers submitted for the scientific conference should be in English. Papers submitted for the industrial conference may be either in English or French. TUTORIALS Tutorials will be organized. The Program Committee is open to proposals for tutorials covering industrial applications. Suggestions should describe the content of the tutorial (in 150-200 words) and the instructor's expertise and experience in the field concerned. The deadline for reception is MAY 15 1995. EXHIBITION >From October 11-13, 1995, the Conference will host a trade fair of commercially available products relating to neural network tools and applications. In addition, advanced prototypes of tools and applications developed by public sector research organizations will be demonstrated. To receive a complete exhibitor's package, please contact the Conference Secretariat at the address indicated. ***************************************************************************** TEAR OFF HERE ***************************************************************************** INFORMATION FORM to be returned to: ICANN'95 1 avenue Newton bp 207 92 142 CLAMART Cedex France Fax: +33 - 1 - 41 28 45 84 ICANN ' 95 Paris, October 9-13, 1995 Last name : .......................................................... First Name : ........................................................ Organization or company : ............................................ ...................................................................... ...................................................................... Postal code/Zip code : ............................................... City : ............................................................... Country : ............................................................ Tel : .................................Fax : ......................... Electronic mail:...................................................... * I wish to attend the O Scientific conference O Industrial conference * I intend to exhibit * I intend to submit a paper Provisional title.................................................... Author (s) : ........................................................ Brief outline of the subject : ...................................... ..................................................................... Category : * Scientific conference O Theory O Algorithms & architectures O Implementations O Cognitive sciences & AI O Neurobiology O Applications ( please specify) * Industrial conference O Tools O Techniques O Applications ( please specify) ***************************************************************************** TEAR OFF HERE ***************************************************************************** STEERING COMMITTEE Chairs F. Fogelman - Sligos (Paris, F) J.C. Rault - C3ST (Paris, F) Scientific Program co-chairs G. Dreyfus - ESPCI (Paris, F) M. Weinfeld - Ecole Polytechnique (Palaiseau, F) Industrial Program chair P. Corsi - CEC (Brussels, B) Tutorials & Publications chair P. Gallinari - Universite P.& M.Curie (Paris, F) SCIENTIFIC PROGRAM COMMITTEE I. Aleksander (UK); L.B. Almeida (P); S.I. Amari (J); M. Berthod (F); E. Bienenstock (USA); C.M. Bishop (UK); L. Bottou (F); J. M. Buhmann (D); S. Canu (F); V. Cerny (SL); M. Cosnard (F); R. De Mori (CAN); R. Eckmiller (D); N. Franceschini (F); S. Gielen (NL); J.P. Haton (F); J. Herault (F); M. Jordan (USA); D. Kayser (F); T. Kohonen (SF); V. Kurkova (CZ); A. Lansner (S); Z. Li (USA); L. Ljung (S); C. von der Malsburg (D); S. Marcos (F); P.Morasso (I); J.P.Nadal(F); E. Oja (SF); P. Peretto (F); C. Peterson (S); L. Personnaz (F); R. Pfeiffer (CH); T. Poggio (USA); P. Puget (F); S. Raudys (LT); H. Ritter (D); M. Saerens ( B); W. von Seelen (D); J.J. Slotine (USA); S. Solla (DK); J.G. Taylor (GB); C. Torras (E); B. Victorri (F); A. Weigend (USA). INDUSTRIAL PROGRAM COMMITTEE (Preliminary) V.Ancona (F); M. Boda (S); B. Braunschweig (F); C. Bishop (UK); J.P. Corriou (F); M. Dougherty (UK); M. Duranton (F); A. Germond (CH); I. Guyon (USA); G. Kuhn (D); H. Noel (F); P. Refenes (UK); S. Thiria (F); C. Wellekens (B); B. Wiggins (UK). **************************************************************************** PROGRAM PLENARY SPEAKERS J. Friedman (USA); M. Kawato (J); T. Kohonen (SF); L. Ljung (S); W. Singer (D) INVITED SPEAKERS C.M. Bishop (UK); H. Bourlard (B); B. Denby (I); I. Guyon (USA); G. Hinton (CAN); A. Konig (D); Y. Le Cun (USA); D. McKay (UK); C. von der Malsburg (D); E. Oja (SF); C. Peterson (S); T. Poggio (USA); S. Raudys (LT); J.G. Taylor (GB); C. Torras (E); V. Vapnik (USA). TUTORIALS C.M. Bishop (UK); L. Bottou (F); J. Friedman (USA); A. Gee (UK); J. Hertz (DK); L. Jackel (USA); L. Ljung (S); E. Oja (SF); L. Personnaz (F); T. Poggio (USA); I. Rivals (F); V. Vapnik (USA). INDUSTRIAL SESSIONS Banking, finance & insurance (P. Refenes); Defense (H. Noel); Document processing, OCR, text retrieval & indexing (I. Guyon); Forecasting & marketing (G. Kuhn); Medicine (J. Demongeot); NN Clubs & Funding Programs (C. Bishop); Oil industry (B. Braunschweig); Power industry (A. Germond); Process engineering, control and monitoring (J.P. Corriou); Robotics (W. von Seelen); Speech processing (C. Wellekens); Telecommunications (M. Boda); Teledetection (S. Thiria); Transportation M. Dougherty); VLSI & dedicated hardware (M. Duranton). ************************************************************************ From wolpert@psyche.mit.edu Sat Mar 4 12:41:32 1995 Received: from cs.wisc.edu by sea.cs.wisc.edu; Sat, 4 Mar 95 12:41:29 -0600; AA24818 Received: from TELNET-1.SRV.CS.CMU.EDU by cs.wisc.edu; Sat, 4 Mar 95 12:41:26 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa06513; 3 Mar 95 15:11:22 EST Received: from GS151.SP.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa06511; 3 Mar 95 14:40:43 EST Received: from GS151.SP.CS.CMU.EDU by GS151.SP.CS.CMU.EDU id aa29463; 3 Mar 95 14:40:13 EST Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa06059; 2 Mar 95 16:19:26 EST Received: from PSYCHE.MIT.EDU by CS.CMU.EDU id aa23997; 2 Mar 95 16:17:58 EST Received: from spoleto.mit.edu.mit.edu by psyche.mit.edu (4.1/DA1.0.4) id AA18741; Thu, 2 Mar 95 16:06:40 EST Date: Thu, 2 Mar 95 16:06:40 EST From: Daniel Wolpert <wolpert@psyche.mit.edu> Message-Id: <9503022106.AA18741@psyche.mit.edu> Received: by spoleto.mit.edu.mit.edu (4.1/SMI-4.1) id AA00168; Thu, 2 Mar 95 16:14:35 EST To: connectionists@cs.cmu.edu Subject: Two NIPS preprints on motor control The following two papers will appear in G. Tesauro, D.S. Touretzky and T.K. Leen, eds., "Advances in Neural Information Processing Systems 7", MIT Press, Cambridge MA, 1995. The papers combine computational and psychophysical approaches to human motor control. Daniel Wolpert wolpert@psyche.mit.edu ----------------------------------------------------------------------- Forward dynamic models in human motor control: Psychophysical evidence Daniel Wolpert, Zoubin Ghahramani & Michael Jordan Department of Brain & Cognitive Sciences Massachusetts Institute of Technology Cambridge, MA 02139 Based on computational principles, with as yet no direct experimental validation, it has been proposed that the central nervous system (CNS) uses an internal model to simulate the dynamic behavior of the motor system in planning, control and learning. We present experimental results and simulations based on a novel approach that investigates the temporal propagation of errors in the sensorimotor integration process. Our results provide direct support for the existence of an internal model. FTP-host: psyche.mit.edu FTP-filename: /pub/wolpert/forward.ps.Z URL: ftp://psyche.mit.edu/pub/wolpert/forward.ps.Z 8 pages long [163K compressed]. ----------------------------------------------------------------------- Computational structure of coordinate transformations: A generalization study Zoubin Ghahramani, Daniel Wolpert & Michael Jordan Department of Brain & Cognitive Sciences Massachusetts Institute of Technology Cambridge, MA 02139 One of the fundamental properties that both neural networks and the central nervous system share is the ability to learn and generalize from examples. While this property has been studied extensively in the neural network literature it has not been thoroughly explored in human perceptual and motor learning. We have chosen a coordinate transformation system---the visuomotor map which transforms visual coordinates into motor coordinates---to study the generalization effects of learning new input--output pairs. Using a paradigm of computer controlled altered visual feedback, we have studied the generalization of the visuomotor map subsequent to both local and context-dependent remappings. A local remapping of one or two input-output pairs induced a significant global, yet decaying, change in the visuomotor map, suggesting a representation for the map composed of units with large functional receptive fields. Our study of context-dependent remappings indicated that a single point in visual space can be mapped to two different finger locations depending on a context variable---the starting point of the movement. Furthermore, as the context is varied there is a gradual shift between the two remappings, consistent with two visuomotor modules being learned and gated smoothly with the context. FTP-host: psyche.mit.edu FTP-filename: /pub/wolpert/coord.ps.Z URL: ftp://psyche.mit.edu/pub/wolpert/coord.ps.Z 8 pages long [218K compressed]. From rjb@psy.ox.ac.uk Sat Mar 4 12:41:34 1995 Received: from cs.wisc.edu by sea.cs.wisc.edu; Sat, 4 Mar 95 12:41:31 -0600; AA24823 Received: from TELNET-1.SRV.CS.CMU.EDU by cs.wisc.edu; Sat, 4 Mar 95 12:41:28 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id ab06513; 3 Mar 95 15:12:08 EST Received: from GS151.SP.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id ab06511; 3 Mar 95 14:40:52 EST Received: from GS151.SP.CS.CMU.EDU by GS151.SP.CS.CMU.EDU id aa29466; 3 Mar 95 14:40:16 EST Received: from EDRC.CMU.EDU by B.GP.CS.CMU.EDU id aa21354; 3 Mar 95 11:20:34 EST Received: from axp01.mrc-bbc.ox.ac.uk by EDRC.CMU.EDU id aa29604; 3 Mar 95 9:17:12 EST Received: (from rjb@localhost) by axp01.mrc-bbc.ox.ac.uk (8.6.10/8.6.10) id OAA05484; Fri, 3 Mar 1995 14:16:15 GMT Date: Fri, 3 Mar 1995 14:16:15 GMT From: Roland Baddeley <rjb@psy.ox.ac.uk> Message-Id: <199503031416.OAA05484@axp01.mrc-bbc.ox.ac.uk> To: Connectionists@cs.cmu.edu Subject: Job available at University of Oxford A new position available that may interest reader of Connectionists. Please feel free to pass to other boards or colleagues, and please send replies to erolls@psy.ox.ac.uk and not to this address. Roland Baddeley UNIVERSITY OF OXFORD DEPARTMENT OF EXPERIMENTAL PSYCHOLOGY Post in Computational Neuroscience The following post is available as part of a long-term research programme combining computational and neurophysiological approaches to the brain mechanisms of vision and memory: Computational neuroscientist (RS1A) to make formal network models and/or analyse by neural network simulation the functions of visual cortical areas and the hippocampus. The salary is on the RS1A (postdoctoral) scale 13,941-20,953 pounds, with support provided by a Programme Grant, and is available from April 1995. Applications including the names of two referees, or enquiries for further details, to Dr. Edmund T. Rolls, University of Oxford, Department of Experimental Psychology, South Parks Road, Oxford OX1 3UD, England (telephone 01865-271348, email erolls@psy.ox.ac.uk). The University is an Equal Opportunities Employer. An introduction to some of the work is provided in the following: Rolls,E.T. and Treves,A. (1994) Neural networks in the brain involved in memory and recall. Progress in Brain Research 102: 335-341. or Treves,A. and Rolls,E.T. (1994) A computational analysis of the role of the hippocampus in memory. Hippocampus 4: 374-391. Rolls,E.T. (1994) Brain mechanisms for invariant visual recognition and learning. Behavioural Processes 33: 113- 138. or Rolls,E.T. (1995) Learning mechanisms in the temporal lobe visual cortex. Behavioural Brain Research 66: 177-185.