From hu@engr.wisc.edu Sun Jul 21 12:06:04 1996 Received: from lucy.cs.wisc.edu (lucy.cs.wisc.edu [128.105.2.11]) by sea.cs.wisc.edu (8.6.12/8.6.12) with ESMTP id MAA11081 for ; Sun, 21 Jul 1996 12:05:52 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.6.12/8.6.12) with SMTP id MAA10573 for ; Sun, 21 Jul 1996 12:05:50 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa21253; 21 Jul 96 12:13:08 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa21251; 21 Jul 96 11:51:50 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa02317; 21 Jul 96 11:51:00 EDT Received: from RI.CMU.EDU by B.GP.CS.CMU.EDU id aa10581; 21 Jul 96 11:48:07 EDT Received: from eceserv0.ece.wisc.edu by RI.CMU.EDU id aa16415; 21 Jul 96 11:47:45 EDT Received: from F182-059.net.wisc.edu by eceserv0.ece.wisc.edu (WE5:5.65c/ES5) id AA24785; Sun, 21 Jul 1996 10:47:32 -0500 Message-Id: <199607211547.AA24785@eceserv0.ece.wisc.edu> Date: Sun, 21 Jul 96 10:47:34 0000 From: "Hu, Yu Hen" Organization: Univ. of Wisconsin X-Mailer: Mozilla 1.1N (Macintosh; I; 68K) Mime-Version: 1.0 To: Connectionists@cs.cmu.edu Subject: CFP: ISMIP'96 (New Submission Deadline) X-Url: newsrc://news.DoIt.wisc.edu/ Content-Transfer-Encoding: 7bit Content-Type: text/plain ------------------------------------------------ CALL FOR PAPERS (Extension of Submission Deadline) ------------------------------------------------ 1996 International Symposium on Multi-Technology Information Processing A Joint Symposium of Artificial Neural Networks, Circuits and Systems, and Signal Processing December 16-18, 1996 Hsin-Chu, Taiwan, Republic of China ************************************************* NEW PAPER SUBMISSION DEADLINE: AUGUEST 5, 1996 ************************************************* Call For Papers --------------- The International Symposium on Multi-Technology Information Processing (ISMIP'96), a joint symposium of artificial neural networks, circuits and systems, and signal processing, will be held in National Tsing Hua University, Hsin Chu, Taiwan, Republic of China. This conference is an expansion of previous series of International Symposium of Artificial Neural Networks (ISANN). The main purpose of this conference is to offer a forum showcasing the latest advancement of modern information processing technologies. It will include recent innovative research results of theories, algorithms, architectures, systems, hardware implementations that lead to intelligent information processing. The technical program will feature opening keynote addresses, invited plenary talks, technical presentations of refereed papers. The official language is English. Papers are solicited for, but not limited to, the following topics: 1. Associative Memory 2. Digital and Analog Neurocomputers 3. Fuzzy Neural Systems 4. Supervised/Un-supervised Learning 5. Robotics 6. Sensory/Motor Control 7. Image Processing 8. Pattern Recognition 9. Language/ Speech Processing 10. Digital Signal Processing 11. VLSI Architectures 12. Non-linear Circuits 13. Multi-media information processing 14. Optimization 15. Mathematical Methods 16. Visual signal processing 17. Content based signal processing 18. Applications Prospective authors are invited to submit 4 copies of extended summaries of no more than 4 pages. All the manuscripts must be written in English in single-spaced, single column, on 8.5" by 11" white papers. The top of the first page of the paper should include a title, authors' names, affiliations, address, telephone/fax numbers, and email address if applicable. The indicated corresponding author will receive an acknowledgement of his/her submission. Camera-ready full papers of accepted manuscripts will be published in a hard-bound proceedings and distributed in the symposium. For more information, please consult at the URL site http://pierce.ee.washington.edu/~nnsp/ismip96.html Authors are invited to send submissions to one of the program co-chairs: ------------------- For submissions from USA and Europe Dr. C.-H. Lee Multimedia Communications Research Lab Bell Laboratories, Lucent Technologies 600 Mountain Ave. 2D-425 Murray Hill, NJ 07974-0636 USA Phone: 908-582-5226 fax: 908-582-7308 chl@research.bell-labs.com --------------------- For submissions from Asia and the rest of the world Prof. V. W. Soo Dept. of Computer Science National Tsing Hua University Hsin Chu, Taiwan 30043, ROC Phone: 886-35-731068 FAX: 886-35-723694 soo@cs.nthu.edu.tw Schedule -------- Submission of full paper: August 5, 1996. Notification of acceptance: September 30, 1996. Submission of camera-ready paper: October 31, 1996. Advanced registration, before: November 15, 1996. Sponsored by National Tsing Hua University (NTHU), Ministry of Education, Taiwan R.O.C. National Science Council, Taiwan R.O.C. in Cooperation with IEEE Signal Processing Society, IEEE Circuits and Systems Society IEEE Neural Networks Council, IEEE Taiwan Section Taiwanese Association for Artificial Intelligence ORGANIZATION ------------ General Co-chairs: H. C. Wang, NTHU Y. H. Hu, U. of Wisconsin Advisory board Co-chairs: W. T. Chen, NTHU S. Y. Kung, Princeton U. Vice Co-chairs: H. C. Hu, NCTU J.N. Hwang, U. of Washington Program Co-chairs: V. W. Soo, NTHU Chin-Hui Lee AT&T From pazzani@super-pan.ICS.UCI.EDU Sun Jul 21 12:33:38 1996 Received: from lucy.cs.wisc.edu (lucy.cs.wisc.edu [128.105.2.11]) by sea.cs.wisc.edu (8.6.12/8.6.12) with ESMTP id MAA11244 for ; Sun, 21 Jul 1996 12:33:28 -0500 Received: from paris.ics.uci.edu (paris.ics.uci.edu [128.195.1.50]) by lucy.cs.wisc.edu (8.6.12/8.6.12) with SMTP id MAA10685; Sun, 21 Jul 1996 12:33:24 -0500 Received: from super-pan.ics.uci.edu by paris.ics.uci.edu id aa02418; 21 Jul 96 9:34 PDT To: ML-LIST:; Subject: Machine Learning List: Vol. 8, No. 13 Reply-to: ml@ics.uci.edu Date: Sun, 21 Jul 1996 09:00:27 -0700 From: Michael Pazzani Message-ID: <9607210934.aa02418@paris.ics.uci.edu> Machine Learning List: Vol. 8, No. 13 Sunday, July 21, 1996 Contents: Predictive Accuracy: Evaluating Algorithms, Representation or Interestingness !? NFL question FISC: Jobs and grants in cognitive science Computational Cognitive Modeling: Source of the Power AAAI-96 WS on IAA (Call For Participation) GP-97 Call for Papers CBR-Works Evaluation for free AIME'97 Second CFP Final CALL for PAPERS PAKDD97 (August 1, 1996) ALifeV-Conf-Report, Hugo de Garis, ATR, Kyoto, Japan REMINDER: WSC1 Special Session ... 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 obtained from http://www.ics.uci.edu/AI/ML/Machine-Learning.html ---------------------------------------------------------------------- Date: Wed, 3 Jul 1996 12:08:58 -0400 From: Ibrahim Imam Subject: Predictive Accuracy: Evaluating Algorithms, Representation or Interestingness !? Ronny> ... The performance Ronny> of simple rules in terms of accuracy can be measured. I am not Ronny> clear why you think this is confusing. ... Ronny> His goal was to show that simple rules are accurate and the Ronny> results show that the absolute differences are not as big as Ronny> some people might have expected (although these results apply Ronny> mostly to small UC Irvine files that existed circa 1990). I sent the following reply (which for some reason did not appear till now) to Gregory Piatetsky-Shapiro's message which was published in the ML List Vol 8. No. 10, (May 30, 1996) under the titled "Applications of Machine Learning Precise Rules are not interesting". I guess the same reply may apply here too. ***** Predictive Accuracy is one of the criteria used by most machine learning researchers to evaluate the performance, consistency, and other behaviors of !learning systems!, and IT SHOULD NOT BE USED TO EVALUATE THE REPRESENTATION, THE QUALITY, OR THE INTERESTINGNESS OF DISCOVERED OR LEARNED KNOWLEDGE. HAVING A HIGH PREDICTIVE ACCURACY MEANS THAT THE LEARNING SYSTEM LEARNED THE CORRECT CONCEPT. This correct concept can be represented in different forms, different organizations of a single representation (e.g., multiple decision trees capture the same concept), different combinations of attributes, etc. We should have different methodology to evaluate the interestingness, effectiveness, and other characteristics of knowledge. I guess the Expert System community has different methodologies for validating and verifying knowledge-bases. Regards, Ibrahim F. Imam SRA International ------------------------------ Date: Fri, 12 Jul 96 14:41:08 EDT From: spears@aic.nrl.navy.mil Subject: NFL question Kohavi>>> 2. There is no free lunch. No algorithm can perform no better than Kohavi>>> any other on average if all targets are equiprobable (Wolpert, Kohavi>>> 1994). Ibrahim>> Does the part "if .." make any difference to the point Ibrahim>> of investigation? Kohavi> This is a theorem and it's false without the "if" part. To use the terminology in our ML95 paper, are you referring to the "Average Generalization Performance", or the "Expected Generalization Performance" (EGP)? If the former, then the NFL theorem will still hold if the targets are not equiprobable, correct? After all, the theorem does not take into account the probability of targets (an average doesn't care about those probabilities). If the latter, then has it been proven that if all targets are not equiprobable that there must be some learner with non-0 EGP? In our ML95 paper we outline symmetry conditions that will yield 0 EGP for all learners. We wondered if these all boil down to the "equiprobable" situation, but we have seen no proof one way or the other. Has there been any more progress on answering this question? Bill, Diana, and Bharat ------------------------------ Date: Sat, 13 Jul 1996 18:28:48 +0200 (MET DST) From: Damien Raczy Subject: FISC: Jobs and grants in cognitive science FISC is a (strictly) moderated mailing-list, distributing announcements of jobs, postdocs, grants,... related to Cognitive Science, for young cognitive scientists. Announcements are mainly european but not only. To post an announcement, send a mail to who will forward it to the list. Please include the following in your subject : position, title, location. To subscribe send a mail to: to : listserv@univ-lille3.fr subject : (null) message : SUBSCRIBE fisc Faithfully Damien Raczy ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Damien Raczy *** FISC Financement et l'Insertion des Jeunes Chercheurs en Sciences Cognitives FISC:en francais (english is coming soon): http://www.univ-lille3.fr/www/fisc/ Une action de l'Association pour la Recherche Cognitive http://www.mines.u-nancy.fr/~arc/ ------------------------------ From: "Charles X. Ling" Date: Thu, 18 Jul 96 02:34:56 HKT Subject: Computational Cognitive Modeling: Source of the Power AAAI-96 Workshop Computational Cognitive Modeling Source of the Power One-day Workshop. August 5, 1996 (During UAI, KDD, AAAI, and IAAI. Portland, Oregon) Visit http://www.cs.hku.hk/~ling for updated info Program Committee: Charles Ling (co-chair), University of Hong Kong, ling@cs.hku.hk Ron Sun (co-chair), University of Alabama, rsun@cs.ua.edu Pat Langley, Stanford University Mike Pazzani, UC Irvine Tom Shultz, McGill University Paul Thagard, Univ. of Waterloo Kurt VanLehn, Univ. of Pittsburgh Invited speakers: Gary Cottrell, Jeff Elman, Denis Mareschal, Tom Shultz, Aaron Sloman, and Paul Thagard. Note: To attend the Workshop, you MUST register. To register, send e-mails to Charles Ling or Ron Sun. If you register the AAAI main conference, registration fee is free (but you still need to register); otherwise, there is a fee of $150 per Workshop. The Workshop Program and Schedule 9:00 am: Welcome and Introduction. Charles Ling and Ron Sun (Co-Chairs) 9:10 am: Aaron Sloman, The University of Birmingham, UK What sort of architecture is required for a human-like agent? (invited talk) 9:40 am: Susan L. Epstein and Jack Gelfand, City University of New York, USA The creation of new problem solving agents from experience with visual features 10:00 am: Denis Mareschal, Exeter University, UK Models of Object Permanence: How and Why they Work (invited talk) 10:30 am: coffee break 11:00 am: Pat Langley, Stanford University, USA An abstract computational model of learning selective sensing skills 11:20 am: Craig S. Miller, Dickinson College, USA The source of graded performance in a symbolic rule-based model 11:40 am: Christian D. Schunn and Lynne M. Reder, Carnegie Mellon University Modeling changes in strategy selections over time 12:00 pm: lunch break 1:30 pm: poster session 2:30 pm: Tom Shultz, McGill University, Montreal, Canada Generative Connectionist Models of Cognitive Development: Why They Work (invited talk) 3:00 pm: Garrison W. Cottrell, University of California, San Diego, USA Selective attention in the acquisition of the past tense (invited talk) 3:30 pm coffee break 4:00 pm: Jeff Elman, University of California, San Diego, USA States and stacks: Doing computation with a recurrent neural network (invited talk) 4:30 pm: Paul Thagard, Univ. of Waterloo, Canada Evaluating Computational Models of Cognition: Notes from the Analogy Wars (invited talk) 5:00 pm: Tony Veale, Barry Smyth, Diarmuid O'Donoghue, Mark Keane Representational myopia in cognitive mapping 5:20 pm: Panel and discussions Panelists: Charles Ling, Ron Sun, Pat Langley, Mike Pazzani. 6:30 pm: end ------------------------------ Date: Tue, 16 Jul 1996 11:39:13 -0400 From: Ibrahim Imam Subject: AAAI-96 WS on IAA (Call For Participation) Call For Participation AAAI-96 International Workshop on Intelligent Adaptive Agents (IAA-96) Sunday, August 4, 1996, Portland, Oregon http://www.mli.gmu.edu/~iimam/iaa96/ws_list.html In Conjunction With the Thirteenth National Conference on Artificial Intelligence AAAI-96 Sponsored by the American Association for Ar tificial Intelligence (AAAI). ************************* (FINAL PROGRAM) SUNDAY AUGUST 4, 1996 8:30 am - 5:30 pm ************************* 8:30 am - 8:45 : Opening Remarks Ibrahim F. Imam ************************* 8:45 - 9:30 : Invited Talk (45 mins.) Session Chair: Yves Kodratoff "Directing Improvisational Actors" Barbara Hayes-Roth, Stanford University, USA ************************* 9:30 - 10:30 : Adaptation in Multi-Agent Environment I Session Chair: Brian Gaines 9:30 - 9:55 : (25 mins.) Adaptive Intelligent Vehicle Modules for Tactical Driving, Rahul Sukthankar, Shumeet Baluja, John Hancock, Dean Pomerleau, and Charles Thorpe, Carnegie Mellon University, USA 9:55 - 10:15 : (20 mins.) Adaptation Using Cases in Cooperative Groups, Thomas Haynes and Sandip Sen, The University of Tulsa, USA ************************* 10:15 - 10:30 : (15 mins.) Session Chair: Sandip Sen Discussion I Multiagent Learning and Adaptation ************************* 10:30 - 10:50 : Break ************************* 10:50 - 11:50 : Intelligent Adaptation Session Chair: Brad Whitehall 10:50 - 11:15 : (25 mins.) Knowledge-Directed Adaptation in Multi-Level Agents, John E. Laird, Douglas J. Pearson, University of Michigan, and Scott B. Huffman, Price Waterhouse Technology Center, USA 11:15 - 11:35 : (20 mins.) Adaptive Methodologies for Intelligent Agents, Ibrahim F. Imam, SRA International, USA 11:35 - 11:50 : (15 mins.) Dynamic Aspects of Statistical Classification, G. Nakhaeizadeh, Daimler-Benz Forschung und Technik (DE), C.C. Taylor, University of Leeds (UK), and G. Kunisch, University of Ulm (DE). ************************* 11:50 - 12:10 pm : (20 mins.) Session Chair: John Laird Discussion II Learning Across Levels ************************* 12:10 pm - 1:10 : Lunch ************************* 1:10 - 1:55 : Invited Talk (45 mins.) Session Chair: George Tecuci "Adaptive Interactions in Societies of Agents" Brian Gaines, University of Calgary, Canada ************************* 1:55 - 3:30 : Information-Based Adaptive Agents Session Chair: John Laird 1:55 - 2:20 : (25 mins.) Autonomous and Adaptive Agents that Gather Information, Daniela Rus, Robert Gray, and David Kotz, Dartmouth College, USA 2:20 - 2:45 : (25 mins.) Intelligent Adaptive Information Agents, Keith Decker, Karia Sycara, and Mike Williamson, Carnegie Mellon University, USA 2:45 - 3:05 : (20 mins.) Sacrificing vs. Salvaging Coherence: An Issue For Adaptive Agents In Information Navigation, Kerstin Voigt, California State University at San Bernardino, USA ************************* 3:05 - 3:30 pm : (25 mins.) Session Chair: Kerstin Voigt Discussion III Subject: Adaptation Maintains The Utility of Agents in Changing Environments ************************* 3:30 - 3:50 : Break ************************* 3:50 - 4:50 : Planning and Modeling in Adaptive Agents Session Chair: Rahul Sukthankar 3:50 - 4:15 : (25 mins.) Learning Reliability Models of Other Agents in a Multiagent System, Costas Tsatsoulis, University of Kansas, and Grace Yee, Lockheed Martin, USA 4:15 - 4:35 : (20 mins.) Using Perception Information For Robot Planning and Execution, Karen Z. Haigh and Manuela M. Veloso, Carnegie Mellon University, USA 4:35 - 4:50 : (15 mins.) Cooperative Agents That Adapt for Seamless Messaging in Heterogeneous Communication Networks, Suhayya Abu-Hakima, Ramiro Liscano, and Roger Impey, National Research Council of Canada, Canada ************************* 4:50 - 5:30 : (15 mins.) Session Chair: Costas Tsatsoulis and Ibrahim Imam Discussion IV Evaluation of the workshop (5 to 10 min.s talks) A list of speakers will be announced at the Workshop ************************* For comments and suggestions, send an email to: e-mail: iimam@verdi.iisd.sra.com < /A> ************************* ------------------------------ Date: Mon, 8 Jul 1996 08:21:26 -0700 (PDT) From: "John R. Koza" Subject: GP-97 Call for Papers CALL FOR PAPERS (Version 1.0) GENETIC PROGRAMMING 1997 CONFERENCE (GP-97) July 13 - 16 (Sunday - Wednesday), 1997 Fairchild Auditorium - Stanford University Stanford, California USA E-MAIL: gp@aaai.org http://www-cs-faculty.stanford.edu/~koza/gp97.html The first genetic programming conference in 1996 will feature 73 papers, 17 poster papers, more than 25 late-breaking papers, 12 tutorials, and 2 invited speakers. With over 220 attendees (as of July 2, 1996), this first conference reflects the rapid growth in this field in which over 600 technical papers have been published since 1992. Topics at the second genetic programming conference to be held on July 13 - 16, 1997 include, but are not limited to, applications of genetic programming, theoretical foundations of genetic programming, implementation issues, technique extensions, use of memory and state, cellular encoding (developmental genetic programming), evolvable hardware, evolvable machine language programs, automated evolution of program architecture, evolution and use of mental models, automatic programming of multi-agent strategies, distributed artificial intelligence, automated circuit synthesis, automatic programming of cellular automata, induction, system identification, control, automated design, compression, image analysis, pattern recognition, molecular biology applications, grammar induction, and parallelization. Genetic programming is an automatic programming technique for evolving computer programs that solve (or approximately solve) problems. Starting with a primordial ooze of thousands of randomly created computer programs composed of programmatic ingredients appropriate to the problem, a population of computer programs is progressively evolved over many generations using the Darwinian principle of survival of the fittest, a sexual recombination operation, and occasional mutation. GENERAL CHAIR: John Koza, Stanford University GP-97 PROGRAM COMMITTEE In formation. A board-based program committee consisting of authors of previously published papers on genetic programming will review the submitted papers on genetic programming. The goal is to ask each reviewer to review about 5 - 6 submitted papers and that each submitted paper receive 5 - 6 reviews. SPECIAL PROGRAM CHAIRS The main focus of the conference (and most 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 special program chairs in the following areas: GENETIC ALGORITHMS CLASSIFIER SYSTEMS EVOLUTIONARY PROGRAMMING EVOLUTION STRATEGIES EVOLVABLE HARDWARE TUTORIALS Tutorials will be held on Sunday July 13, 1997. Brief proposals for tutorials are hereby solicited and should be sent to koza@cs.stanford.edu INFORMATION FOR SUBMITTING PAPERS: The deadline for receipt at the physical mail address below of eight (8) copies of each submitted paper is Wednesday, January 8, 1997. Papers are to be in single-spaced, 10-point type on 8 1/2" x 11" paper with 1" margin at top and 3/4" margin at left, right, and bottom. A4 paper may be used, but not e-mail or fax. Papers are to contain ALL of the following 9 items, within a maximum total of 9 pages, IN THIS ORDER: (1) the paper's category (chosen from one of the following six alternatives: genetic programming, genetic algorithms, classifier systems, evolutionary programming, evolution strategies, or evolvable hardware), (2) title of paper, (3) author name(s), (4) author physical address(es), (5) author e-mail address(es), (6) author phone number(s), (7) a 50-200 word abstract of the paper, (8) the text of the paper (including all figures, tables, acknowledgments, and appendices, if any), and (9) bibliography. Review criteria will include significance of the work, novelty, sufficiency of information to permit replication (if applicable), clarity, and writing quality. The first-named (or other designated) author will be notified of acceptance or rejection by approximately six weeks after the deadline for submitting papers. The style of the camera-ready paper will be identical to that of the Genetic Programming 1996 Conference published by the MIT Press (as described in the 4-page instruction paper on the conference's WWW site). Different numbers of pages may be allocated to various accepted papers (e.g., in 1996, there were 9 page papers, 6 page papers, and 1-page poster papers in the proceedings). The deadline for final camera-ready, revised version of accepted papers will be about three weeks after notification of acceptance and will be announced. Proceedings will be distributed at the conference (and, if requested, mailed at no extra charge by 2-day priority mail to registered conference attendees with U.S. addresses about two weeks prior to the conference). By submitting a paper, the author(s) agree that at least one author will register, attend, and present each accepted and published paper at the conference. FOR MORE INFORMATION: GP-97 Conference c/o American Association for Artificial Intelligence 445 Burgess Drive Menlo Park, California 94025 USA PHONE: 415-328-3123. FAX: 415-321-4457 WWW: http://www.aaai.org/ E-MAIL: gp@aaai.org John Koza Koza@cs.stanford.edu http://www-cs-faculty.stanford.edu/~koza/ ------------------------------ Date: Tue, 02 Jul 1996 17:19:16 +0200 From: Wolfgang Wilke Subject: CBR-Works Evaluation for free Case-Based Reasoning CBR-Works: Free Evaluation Prototype Available ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The University of Kaiserslautern provides an evaluation prototype of the commercial CBR shell "CBR-Works". The use of the CBR-Works prototype is free for non-commercial, especially for scientific, usage. The prototype is the outcome of the project "WiMo: Modelling and Acquisition of Knowledge for Case-based Reasoning" (funded by the ministry of economy as part of "Stiftung Rheinland-Pfalz fuer Innovation"). This project was carried out at the University of Kaiserslautern in tight collaboration with tecInno GmbH. The goal of this project was to improve case-based reasoning methods for decision support and classification tasks, developed at the University of Kaiserslautern based on INRECA technology, for their practical industrial use (partners of the INRECA Esprit project P6322 are: AcknoSoft (prime contractor, France), tecInno (Germany), Irish Medical Systems (Ireland) and University of Kaiserslautern (Germany)). A licensed extended version for commercial usage is available from: tecInno GmbH Sauerwiesen 2, D-67661 Kaiserslautern, Germany Phone: ++49 6301/6060; Fax: ++49 6301/60666 Email: trappi@tecmath.de Features of the Prototype ~~~~~~~~~~~~~~~~~~~~~~~~~ CBR-Works is a domain-independent case-based reasoning shell. Some of the key features are: - Fully functional case-based reasoning system - Object-oriented case representation - User defined types and similarity measures - Import facilities for case bases in CASUEL or Execl format - Case filters and user weights - HTML-annotations for cases - Context sensitive online-help Requirements ~~~~~~~~~~~~ - Sun Sparc with SunOS 4.x.x or Solaris 2.4, 32MB memory or - IBM compatible PC with 8MB (16 MB recommended), processor (486 or higher), and Windows 3.1, Windows 3.1.1 or Windows 95 How to Order ~~~~~~~~~~~~ You may have a preview of the system and you can directly order the prototype from the WorldWideWeb. Just look at http://wwwagr.informatik.uni-kl.de/~cbrworks Questions and Comments ~~~~~~~~~~~~~~~~~~~~~~ For questions and comments, send email to: cbrworks@informatik.uni-kl.de Wolfgang Wilke and Ralph Bergmann ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Wolfgang Wilke Office: + 49 631 205 3363 University of Kaiserslautern Sekr.: + 49 631 205 3362 Department of Computer Science Fax: + 49 631 205 3357 Centre for Learning Systems and Applications (LSA) Postfach 3049 D-67653 Kaiserslautern Germany E-mail: wilke@informatik.uni-kl.de WWW: http://wwwagr.informatik.uni-kl.de/~wilke ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ------------------------------ Date: Fri, 5 Jul 1996 08:41:36 +0000 From: Catherine.Garbay@imag.fr Subject: AIME'97 Second CFP AIME'97 6th Conference on Artificial Intelligence in Medicine Europe 23rd - 26th March 1997 Grenoble, France WWW: http://www-timc.imag.fr/aime97 ------------------------------ From: Liu Huan Subject: Final CALL for PAPERS PAKDD97 (August 1, 1996) Date: Tue, 9 Jul 1996 09:03:38 +0800 (GMT-8) =============Deadline (August 1, 1996) is approaching=================== FIRST PACIFIC-ASIA CONFERENCE on KNOWLEDGE DISCOVERY and DATA MINING (PAKDD97) Singapore, 23-24 February, 1997 (Co-located with 2nd Pacific-Asia Conference on Expert Systems/ 3rd Singapore International Conference on Intelligent Systems) http://www.iscs.nus.sg/conferences/pakdd97.html ------------------------------ From: Hugo de Garis Date: Wed, 10 Jul 96 17:07:37 JST Subject: ALifeV-Conf-Report, Hugo de Garis, ATR, Kyoto, Japan A report on the ALife V conference can be seen on the web at URL - http://www.hip.atr.co.jp/~degaris ------------------------------ From: R Roy Date: Thu, 11 Jul 1996 13:15:01 BST Subject: REMINDER: WSC1 Special Session ... 1st On-line Workshop on SOFT COMPUTING (WSC1) August 19 (Mon.) - 30 (Fri.), 1996 REMINDER REMINDER REMINDER REMINDER LAST DATE OF PAPER SUBMISSION: 5th Aug. '96 WWW Home Page: http://www.tech.plym.ac.uk/wsc/wsc1.htm For further queries please contact: wscplym@soc.plym.ac.uk ------------------------------ End of ML-LIST (Digest format) **************************************** From listerrj@helios.aston.ac.uk Wed Jul 24 11:46:03 1996 Received: from lucy.cs.wisc.edu (lucy.cs.wisc.edu [128.105.2.11]) by sea.cs.wisc.edu (8.6.12/8.6.12) with ESMTP id LAA11612 for ; Wed, 24 Jul 1996 11:45:55 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.6.12/8.6.12) with SMTP id LAA22259 for ; Wed, 24 Jul 1996 11:45:53 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa24519; 24 Jul 96 11:46:05 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa24502; 24 Jul 96 11:08:57 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa05071; 24 Jul 96 11:08:28 EDT Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa20865; 24 Jul 96 9:25:39 EDT Received: from email.aston.ac.uk by CS.CMU.EDU id aa05720; 24 Jul 96 9:25:14 EDT Received: from sun.aston.ac.uk (actually host dirac.aston.ac.uk) by email.aston.ac.uk with SMTP (PP); Wed, 24 Jul 1996 14:27:22 +0100 Message-Id: <13421.199607241323@sun.aston.ac.uk> To: Connectionists@cs.cmu.edu Subject: Two Postdoctoral Research Fellowships X-Mailer: Mew version 1.02 on Emacs 19.29.2 Mime-Version: 1.0 Content-Type: Text/Plain; charset=us-ascii Date: Wed, 24 Jul 1996 14:23:07 +0100 From: Richard Lister ---------------------------------------------------------------------- Neural Computing Research Group ------------------------------- Dept of Computer Science and Applied Mathematics Aston University, Birmingham, UK TWO POSTDOCTORAL RESEARCH FELLOWSHIPS ------------------------------------- *** Full details at http://www.ncrg.aston.ac.uk/ *** ---------------------------------------------------------------------- Analysis of On-Line Learning in Neural Networks ----------------------------------------------- The Neural Computing Research Group at Aston is looking for a highly motivated individual for a 2 year postdoctoral research position in the area of `Analysis of On-Line Learning in Neural Networks'. The emphasis of the research will be on applying a theoretically well- founded approach based on methods adopted from statistical mechanics to analyse learning in multilayer perceptrons in various learning scenarios. Potential candidates should have strong mathematical and computational skills, with a background in statistical mechanics and neural networks. Conditions of Service --------------------- Salaries will be up to point 6 on the RA 1A scale, currently 15,986 UK pounds. The salary scale is subject to annual increments. How to Apply ------------ If you wish to be considered for this Fellowship, please send a full CV and publications list, including full details and grades of academic qualifications, together with the names of 3 referees, to: Dr. David Saad Neural Computing Research Group Dept. of Computer Science and Applied Mathematics Aston University Birmingham B4 7ET, U.K. Tel: 0121 333 4631 Fax: 0121 333 6215 e-mail: D.Saad@aston.ac.uk e-mail submission of postscript files is welcome. Candidates that applied for the position `On-line Learning in Radial Basis Function Networks' will be automatically considered for this position as well. Closing date: 12 August, 1996. ---------------------------------------------------------------------- NEUROSAT: Processing of environment observing satellite data ------------------------------------------------------------ with Neural Networks -------------------- The Neural Computing Research Group at Aston is looking for a highly motivated individual for a 3 year postdoctoral research position in the area of processing environmental data from satellites with neural networks, working with Dr. Ian Nabney. The post is funded by a grant from the European Commission Directorate General XII in Environment and Climate. Candidates should have strong mathematical and computational skills, with a background in one or more of neural networks, Bayesian inference, or satellite data analysis. NEUROSAT is a three collaborative project whose objective is to contribute to an enhanced analysis of the real Earth climate driving forces. The consortium is led by Michel Crepon at the Institut Pierre-Simon-Laplace (IPSL) in Paris, and includes partners from the UK, France, Germany and Italy. Aston will be involved in two work packages: Assessment of Generic Techniques and Inferring Sea Surface Wind from Scatterometric Measurements. In the first of these, we are responsible for contributions to survey papers, for technology transfer to other partners, and for some feasibility studies in the use of neural networks in climatological problems. The second work package, which will be the main activity, involves developing some existing research on scatterometric data analysis to a state where it can be compared with the current operational system (AEOLUS) used at the Meteorological Office. The data that will be used comes from the ERS1 satellite. A two stage approach will be applied. The first stage is to improve the local modelling (i.e. the wind vector in a single cell), and the second stage is to improve the global modelling (i.e. the overall wind field). To improve the local modelling, the influence of sea state on the scatterometer signals will be studied. This will be done by using the ERS1 signal collocated with wind vector and sea state obtained from analysed fields of meteorological models and fused with in situ buoy observations. The purpose of this work is to understand the factors involved in the GMF so as to improve the inverse function modelling. Earlier work at Aston has used mixture density networks to model the conditional density of the inverse function (since this is typically multi-valued for wind direction), and this will make it easier to incorporate probabilistic information into the global model. Such information includes priors on model parameters, priors on data coming from weather stations and climatological information (e.g. long term weather trends). This will also allow the wind-field to be `seeded' with known values at specific locations. Techniques from optical flow (for example, div-curl splines) and Bayesian models will be investigated for their application to modelling the global wind field. This approach should lead to a self consistent, accurate and fast neural network procedure to retrieve the entire wind field. This information will be useful to meteorological centres to be assimilated into their prediction models. Dr. David Offiler (of the UK Meteorological Office) will act as a consultant to the project, assisting in the development of prior models and the assessment of the prediction methods. If we can improve on existing techniques, then there is every prospect of replacing them in operational use. Informal enquiries can be made to Ian Nabney (I.T.Nabney@aston.ac.uk). The target start date is September 1996, although this may be somewhat flexible. Conditions of Service --------------------- Salaries will be up to point 6 on the RA 1A scale, currently 15,986 UK pounds. These salary scales are subject to annual increments. How to Apply ------------ If you wish to be considered for this position, please send a full CV and publications list, together with the names of 3 referees, to: Dr. Ian Nabney Neural Computing Research Group Department of Computer Science and Applied Mathematics Aston University Birmingham B4 7ET, U.K. Tel: +44 121 333 4631 Fax: +44 121 333 4586 e-mail: I.T.Nabney@aston.ac.uk (email submission of postscript files is welcome) Closing date: 12 August, 1996. ---------------------------------------------------------------------- From robert@physik.uni-wuerzburg.de Wed Jul 24 11:46:04 1996 Received: from lucy.cs.wisc.edu (lucy.cs.wisc.edu [128.105.2.11]) by sea.cs.wisc.edu (8.6.12/8.6.12) with ESMTP id LAA11610 for ; Wed, 24 Jul 1996 11:45:53 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.6.12/8.6.12) with SMTP id LAA22257 for ; Wed, 24 Jul 1996 11:45:51 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id ab24500; 24 Jul 96 11:37:03 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id ab24498; 24 Jul 96 11:08:06 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa05065; 24 Jul 96 11:07:38 EDT Received: from EDRC.CMU.EDU by B.GP.CS.CMU.EDU id aa20278; 24 Jul 96 7:55:48 EDT Received: from wptx01.physik.uni-wuerzburg.de by EDRC.CMU.EDU id aa06792; 24 Jul 96 7:55:38 EDT Received: (from smap@localhost) by wptx01.physik.uni-wuerzburg.de (8.7.5/8.7.3/TPhys_S) id NAA26654 for ; Wed, 24 Jul 1996 13:55:03 +0200 (MESZ) Received: from wptx15.physik.uni-wuerzburg.de(132.187.40.15) by wptx01.physik.uni-wuerzburg.de (smap V1.3) id sma026650 for ; Wed Jul 24 13:54:58 1996 Date: Wed, 24 Jul 1996 13:54:58 +0200 (MESZ) From: Robert Urbanczik Reply-To: Robert Urbanczik To: Connectionists@cs.cmu.edu Subject: paper available: learning in a committee machine Message-ID: MIME-Version: 1.0 Content-Type: TEXT/PLAIN; charset=US-ASCII FTP-host: ftp.physik.uni-wuerzburg.de FTP-filename: /pub/preprint/WUE-ITP-96-013.ps.gz **DO NOT FORWARD TO OTHER GROUPS** The following paper (9 pages, to appear in Europhys.Letts.) is now available via anonymous ftp: (See below for the retrieval procedure) --------------------------------------------------------------------- Learning in a large committee machine: Worst case and average case by R. Urbanczik Abstract: Learning of realizable rules is studied for tree committee machines with continuous weights. No nontrivial upper bound exists for the generalization error of consistent students as the number of hidden units $K$ increases. However, numerical considerations show that consistent students with a value of the generalization error significantly higher than predicted by the average case analysis are extremely hard to find. An on-line learning algorithm is presented, for which the generalization error scales with the training set size as in the average case theory in the limit of large $K$. --------------------------------------------------------------------- Retrieval procedure: unix> ftp ftp.physik.uni-wuerzburg.de Name: anonymous Password: {your e-mail address} ftp> cd pub/preprint/1996 ftp> get WUE-ITP-96-013.ps.gz ftp> quit unix> gunzip WUE-ITP-96-013.ps.gz e.g. unix> lp WUE-ITP-96-013.ps _____________________________________________________________________ From gluck@pavlov.rutgers.edu Wed Jul 24 18:54:31 1996 Received: from lucy.cs.wisc.edu (lucy.cs.wisc.edu [128.105.2.11]) by sea.cs.wisc.edu (8.6.12/8.6.12) with ESMTP id SAA22015 for ; Wed, 24 Jul 1996 18:54:13 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.6.12/8.6.12) with SMTP id SAA29219 for ; Wed, 24 Jul 1996 18:54:11 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa24500; 24 Jul 96 11:36:05 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa24498; 24 Jul 96 11:08:05 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa05060; 24 Jul 96 11:07:16 EDT Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa20436; 24 Jul 96 8:30:48 EDT Received: from james.rutgers.edu by CS.CMU.EDU id aa05383; 24 Jul 96 8:30:05 EDT Received: (from gluck@localhost) by james.rutgers.edu (8.6.12+bestmx+oldruq+newsunq+grosshack/8.6.12) id IAA01635 for connectionists@cs.cmu.edu; Wed, 24 Jul 1996 08:49:22 -0400 Date: Wed, 24 Jul 1996 08:49:22 -0400 From: Mark Gluck Message-Id: <199607241249.IAA01635@james.rutgers.edu> To: connectionists@cs.cmu.edu Subject: Programmer/R.A. Position at Rutgers Univ, NJ, in Computational Neuro. SEEKING A PROGRAMMER/RESEARCH ASSISTANT TO WORK ON NEURAL-NETWORK BRAIN MODELS AT RUTGERS-NEWARK NEUROSCIENCE CENTER (GLUCK LAB). We are looking for a programmer/research assistant to work with us on testing computational models of cortico-hippocampal function in animal and human learning. The applicant must be able to work independently -- given a set of specifications, he/she should be able to optimize program performance to generate results, and also analyze system behavior. The ideal applicant would be someone recently out of college, who would like some research experience prior to future graduate work in psychology, neuroscience, cognitive science, or computer science. Required Skills: Strong C (or C++) programming Knowledge of Unix Commitment to at least 15 hours/week, for at least one year. Could also be a full time position. Preferrred But Not Required Skills: Knowledge of Sun workstations Background in neural networks Background in premed, biology, or psychology. Salary: Commensurate with skill level and experience. For more information on our research, see our lab WWW page noted below. Contact Mark Gluck below with a cover letter and resume (preferably sent by email) to apply. _______________________________________________________________________________ Dr. Mark A. Gluck Center for Molecular & Behavioral Neuroscience Rutgers University 197 University Ave. Newark, New Jersey 07102 Phone: (201) 648-1080 (Ext. 3221) Fax: (201) 648-1272 Email: gluck@pavlov.rutgers.edu WWW Homepage: http://www.cmbn.rutgers.edu/cmbn/faculty/gluck.html _______________________________________________________________________________ From mel@quake.usc.edu Thu Jul 25 03:27:40 1996 Received: from lucy.cs.wisc.edu (lucy.cs.wisc.edu [128.105.2.11]) by sea.cs.wisc.edu (8.6.12/8.6.12) with ESMTP id DAA01711 for ; Thu, 25 Jul 1996 03:27:32 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.6.12/8.6.12) with SMTP id DAA04653 for ; Thu, 25 Jul 1996 03:27:30 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa25264; 24 Jul 96 18:54:35 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa25261; 24 Jul 96 18:45:16 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa05284; 24 Jul 96 18:44:33 EDT Received: from RI.CMU.EDU by B.GP.CS.CMU.EDU id aa00259; 24 Jul 96 18:18:44 EDT Received: from [128.125.104.79] by RI.CMU.EDU id aa02339; 24 Jul 96 18:17:49 EDT Received: by quake.usc.edu (5.0/8.6.4) id AA21433 for connectionists@cs.cmu.edu; Wed, 24 Jul 1996 15:15:23 +0800 Date: Wed, 24 Jul 1996 15:15:23 +0800 From: Bartlett Mel Message-Id: <9607242215.AA21433@quake.usc.edu> To: connectionists@cs.cmu.edu Subject: Workshop Announcement content-length: 1685 ************* CALL FOR WORKSHOP PARTICIPATION ************* Advanced Workshop on BIOLOGICAL AND ARTIFICIAL NEURAL NETWORKS: A SEARCH FOR SYNERGY sponsored by The USC Biomedical Simulations Resource and The National Center for Research Resources of NIH September 20-21, 1996 Summer House Inn, La Jolla, California This workshop will bring together investigators who share an interest in methodological issues relating to the combined study of biological and artificial neural networks, including innovative uses for artificial neural network techniques in the study of biological neural systems, and novel applications of neurobiologically inspired artificial neural network architectures. Workshop topics will emphasize: * methods for quantitative study of nonstationarities in neural systems * methods for analyzing high-dimensional spatio-temporal neural dynamics * methods for study of dynamic nonlinearities in neural systems Presentations will emphasize practical methodologies. The format will consists of brief invited and contributed presentations (15-20 minutes), followed by extended question/discussion periods emphasizing audience participation. The Workshop has been scheduled in space-time proximity to the World Congress on Neural Networks (San Diego, Sept. 15-19). Registration is free, but advance registration is required as space is limited. Limited funds are available for speakers upon request. To suggest yourself as a contributor, or for additional information, please contact Ms. Stephanie Braun at braun@bmsrs.usc.edu or (213)740-0342. ORGANIZERS: V.Z. Marmarelis, T.W. Berger From marney@ai.mit.edu Thu Jul 25 03:27:42 1996 Received: from lucy.cs.wisc.edu (lucy.cs.wisc.edu [128.105.2.11]) by sea.cs.wisc.edu (8.6.12/8.6.12) with ESMTP id DAA01713 for ; Thu, 25 Jul 1996 03:27:33 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.6.12/8.6.12) with SMTP id DAA04655 for ; Thu, 25 Jul 1996 03:27:32 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa25379; 24 Jul 96 19:56:47 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa25375; 24 Jul 96 19:48:35 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa05351; 24 Jul 96 19:48:07 EDT Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa01483; 24 Jul 96 19:43:12 EDT Received: from life.ai.mit.edu by CS.CMU.EDU id aa11453; 24 Jul 96 19:42:57 EDT Received: from motor-cortex.ai.mit.edu (MOTOR-CORTEX.MIT.EDU) by life.ai.mit.edu (4.1/AI-4.10) for Connectionists@cs.cmu.edu id AA11048; Wed, 24 Jul 96 19:41:47 EDT From: Marney Smyth Received: by motor-cortex.ai.mit.edu (4.1/AI-4.10) id AA00934; Wed, 24 Jul 96 19:41:45 EDT Message-Id: <9607242341.AA00934@motor-cortex.ai.mit.edu> Subject: Intensive Tutorial: Learning Methods for Prediction, Classification To: Connectionists@cs.cmu.edu Date: Wed, 24 Jul 1996 19:41:44 -0400 (EDT) Cc: Marney Smyth X-Mailer: ELM [version 2.4 PL25] Mime-Version: 1.0 Content-Type: text/plain; charset=US-ASCII Content-Transfer-Encoding: 7bit Content-Length: 5071 ************************************************************** *** *** *** Learning Methods for Prediction, Classification, *** *** Novelty Detection and Time Series Analysis *** *** *** *** Cambridge, MA, September 20-21, 1996 *** *** Los Angeles, CA, December 14-15, 1996 *** *** *** *** Geoffrey Hinton, University of Toronto *** *** Michael Jordan, Massachusetts Inst. of Tech. *** *** *** ************************************************************** A two-day intensive Tutorial on Advanced Learning Methods will be held on September 20 and 21, 1996, at the Royal Sonesta Hotel, Cambridge, MA, and on December 14 and 15, 1996, at Lowe's Hotel, Santa Monica, CA. Space is available for up to 50 participants for each course. The course will provide an in-depth discussion of the large collection of new tools that have become available in recent years for developing autonomous learning systems and for aiding in the analysis of complex multivariate data. These tools include neural networks, hidden Markov models, belief networks, decision trees, memory-based methods, as well as increasingly sophisticated combinations of these architectures. Applications include prediction, classification, fault detection, time series analysis, diagnosis, optimization, system identification and control, exploratory data analysis and many other problems in statistics, machine learning and data mining. The course will be devoted equally to the conceptual foundations of recent developments in machine learning and to the deployment of these tools in applied settings. Case studies will be described to show how learning systems can be developed in real-world settings. Architectures and algorithms will be presented in some detail, but with a minimum of mathematical formalism and with a focus on intuitive understanding. Emphasis will be placed on using machine methods as tools that can be combined to solve the problem at hand. WHO SHOULD ATTEND THIS COURSE? The course is intended for engineers, data analysts, scientists, managers and others who would like to understand the basic principles underlying learning systems. The focus will be on neural network models and related graphical models such as mixture models, hidden Markov models, Kalman filters and belief networks. No previous exposure to machine learning algorithms is necessary although a degree in engineering or science (or equivalent experience) is desirable. Those attending can expect to gain an understanding of the current state-of-the-art in machine learning and be in a position to make informed decisions about whether this technology is relevant to specific problems in their area of interest. COURSE OUTLINE Overview of learning systems; LMS, perceptrons and support vectors; generalized linear models; multilayer networks; recurrent networks; weight decay, regularization and committees; optimization methods; active learning; applications to prediction, classification and control Graphical models: Markov random fields and Bayesian belief networks; junction trees and probabilistic message passing; calculating most probable configurations; Boltzmann machines; influence diagrams; structure learning algorithms; applications to diagnosis, density estimation, novelty detection and sensitivity analysis Clustering; mixture models; mixtures of experts models; the EM algorithm; decision trees; hidden Markov models; variations on hidden Markov models; applications to prediction, classification and time series modeling Subspace methods; mixtures of principal component modules; factor analysis and its relation to PCA; Kalman filtering; switching mixtures of Kalman filters; tree-structured Kalman filters; applications to novelty detection and system identification Approximate methods: sampling methods, variational methods; graphical models with sigmoid units and noisy-OR units; factorial HMMs; the Helmholtz machine; computationally efficient upper and lower bounds for graphical models REGISTRATION Standard Registration: $700 Student Registration: $400 Registration fee includes course materials, breakfast, coffee breaks, and lunch on Saturday. Those interested in participating should return the completed Registration Form and Fee as soon as possible, as the total number of places is limited by the size of the venue. ADDITIONAL INFORMATION A registration form is available from the course's WWW page at http://www.ai.mit.edu/projects/cbcl/web-pis/jordan/course/index.html Marney Smyth CBCL at MIT E25-201 45 Carleton Street Cambridge, MA 02142 USA Phone: 617 253-0547 Fax: 617 253-2964 E-mail: marney@ai.mit.edu From tvogl@wo.erim.org Thu Jul 25 13:56:09 1996 Received: from lucy.cs.wisc.edu (lucy.cs.wisc.edu [128.105.2.11]) by sea.cs.wisc.edu (8.6.12/8.6.12) with ESMTP id NAA16053 for ; Thu, 25 Jul 1996 13:55:59 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.6.12/8.6.12) with SMTP id NAA13071 for ; Thu, 25 Jul 1996 13:55:55 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa27207; 25 Jul 96 11:37:42 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa27204; 25 Jul 96 11:17:16 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa06038; 25 Jul 96 11:16:41 EDT Received: from RI.CMU.EDU by B.GP.CS.CMU.EDU id aa10537; 25 Jul 96 9:12:09 EDT Received: from [38.250.219.10] by RI.CMU.EDU id aa05291; 25 Jul 96 9:11:58 EDT Received: by wopia.wo.erim.org (920330.SGI/SMI-4.1) id AA09440; Thu, 25 Jul 96 09:03:07 -0400 Date: Thu, 25 Jul 1996 09:03:07 +30000 From: "Thomas P. Vogl" To: connectionists@cs.cmu.edu Subject: Postdoc. Fellowship Available Message-Id: Mime-Version: 1.0 Content-Type: TEXT/PLAIN; charset=US-ASCII Postdoctoral Research Fellowship at George Mason University (GMU), Molecular Biosciences and Technology Institute (MBTI). Applications are invited for a postdoctoral Fellowship in the area of development of self-organizing pattern recognition algorithms based on biological information processing in visual and IT cortex. The aims of the project are (1) to develop neurobiologically plausible algorithms of visual pattern recognition which are computationally efficient and robust, and (2) compare performance of resulting algorithms with human performance in order to develop hypotheses about information processing in the brain. Evaluation of algorithms is performed using real world problems (e.g. face recognition and optical character recognition), and by comparison to human observer pattern recognition performance. We are seeking an individual with background in both neurobiology and computer science (good UNIX and C or C++ skills). Working knowledge of information theory or mathematical statistics is highly desirable but not required. The position is for one year, beginning October 1, 1996, with possible renewal for an additional three years. The initital stipend is $30,000/year plus fringe benefits. Our decade-old group currently consists of Drs. T.P. Vogl and K.T. Blackwell, and two graduate students, all of whom are actively involved in ongoing collaboration among neuroscientists (electrophysiologists) at NINDS/NIH; members of the GMU faculty in MBTI, several Departments, and the Krasnow Institute at GMU; and the professional staff at the Environmental Research Institute of Michigan (ERIM), a not-for-profit R&D company associated with the University of Michigan. Research activities encompass computer modeling, particularly computational neurobiology at levels ranging from channel level modeling of learning in single neurons to network level models, and visual psychophysics. To apply for this position, send your curriculum vitae and at least two letters of reference (in ASCII or MIME attached PostScript formats only) before September 1, 1996, to Prof. Thomas P. Vogl email: tvogl@gmu.edu. snail-mail to: ERIM 1101 Wilson Blvd. Ste 1100 Arlington, VA 22209 From listerrj@helios.aston.ac.uk Thu Jul 25 21:55:16 1996 Received: from lucy.cs.wisc.edu (lucy.cs.wisc.edu [128.105.2.11]) by sea.cs.wisc.edu (8.6.12/8.6.12) with ESMTP id VAA25368 for ; Thu, 25 Jul 1996 21:55:07 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.6.12/8.6.12) with SMTP id VAA19845 for ; Thu, 25 Jul 1996 21:55:04 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id ab27608; 25 Jul 96 15:18:07 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id ab27605; 25 Jul 96 15:07:59 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa06151; 25 Jul 96 15:06:25 EDT Received: from EDRC.CMU.EDU by B.GP.CS.CMU.EDU id aa13674; 25 Jul 96 12:20:42 EDT Received: from email.aston.ac.uk by EDRC.CMU.EDU id aa13715; 25 Jul 96 12:20:32 EDT Received: from sun.aston.ac.uk (actually host dirac.aston.ac.uk) by email.aston.ac.uk with SMTP (PP); Thu, 25 Jul 1996 17:22:49 +0100 Message-Id: <15572.199607251618@sun.aston.ac.uk> To: Connectionists@cs.cmu.edu Subject: Postdoctoral Research Fellowship X-Mailer: Mew version 1.02 on Emacs 19.29.2 Mime-Version: 1.0 Content-Type: Text/Plain; charset=us-ascii Date: Thu, 25 Jul 1996 17:18:37 +0100 From: Richard Lister ---------------------------------------------------------------------------- Neural Computing Research Group ------------------------------- Dept of Computer Science and Applied Mathematics Aston University, Birmingham, UK POSTDOCTORAL RESEARCH FELLOWSHIP -------------------------------- *** Full details at http://www.ncrg.aston.ac.uk/ *** "Dynamical Systems and Information Geometric Approaches to Generalization" -------------------------------------------------------------------------- A mathematically-oriented researcher is required to work on a project examining a geometric view of generalization in neural networks. Geometry and topology occur at two levels in network models. A dynamical systems perspective is required to examine the behaviour of an individual neural network structure, and an information geometric perspective is required to examine the space of neural network models and perform inference. In both cases the role and geometrization of prior knowledge guides the generalization. The aim of this project is to investigate the issues of generalization in neural networks based on the geometric properties of dynamical systems, and information geometry spaces. This project forms part of a larger research activity on Validation and Verification of Neural Networks. Conditions of Service --------------------- Salaries will be up to point 6 on the RA 1A scale, currently 15,986 UK pounds. The salary scale is subject to annual increments. How to Apply ------------ If you wish to be considered for this Fellowship, please send a full CV and publications list, including full details and grades of academic qualifications, together with the names of 3 referees, to: Professor David Lowe Neural Computing Research Group Dept. of Computer Science and Applied Mathematics Aston University Birmingham B4 7ET, U.K. Tel: 0121 333 4631 Fax: 0121 333 6215 e-mail: D.Lowe@aston.ac.uk e-mail submission of postscript files is welcome. Candidates that applied for this Fellowship will also automatically be considered for the four other postdoctoral Fellowships currently offered by the Neural Computing Research Group. Closing date: 19 August, 1996. ---------------------------------------------------------------------------- From radford@cs.toronto.edu Thu Jul 25 21:55:17 1996 Received: from lucy.cs.wisc.edu (lucy.cs.wisc.edu [128.105.2.11]) by sea.cs.wisc.edu (8.6.12/8.6.12) with ESMTP id VAA25370 for ; Thu, 25 Jul 1996 21:55:08 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.6.12/8.6.12) with SMTP id VAA19847 for ; Thu, 25 Jul 1996 21:55:06 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa27821; 25 Jul 96 17:16:27 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa27818; 25 Jul 96 17:06:14 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa06246; 25 Jul 96 17:06:03 EDT Received: from RI.CMU.EDU by B.GP.CS.CMU.EDU id aa18266; 25 Jul 96 17:05:09 EDT Received: from yonge.cs.toronto.edu by RI.CMU.EDU id aa07750; 25 Jul 96 17:04:15 EDT Received: from neuron.ai.toronto.edu ([128.100.3.14]) by yonge.cs.toronto.edu with SMTP id <86571>; Thu, 25 Jul 1996 17:03:33 -0400 Received: by neuron.ai.toronto.edu id <1282>; Thu, 25 Jul 1996 17:03:19 -0400 From: Radford Neal To: connectionists@cs.cmu.edu Subject: TR on Factor Analysis Using Delta-Rule Wake-Sleep Learning Message-Id: <96Jul25.170319edt.1282@neuron.ai.toronto.edu> Date: Thu, 25 Jul 1996 17:03:11 -0400 Technical Report Available FACTOR ANALYSIS USING DELTA-RULE WAKE-SLEEP LEARNING Radford M. Neal Dept. of Statistics and Dept. of Computer Science University of Toronto Peter Dayan Department of Brain and Cognitive Sciences Massachusetts Institute of Technology 24 July 1996 We describe a linear network that models correlations between real-valued visible variables using one or more real-valued hidden variables - a *factor analysis* model. This model can be seen as a linear version of the "Helmholtz machine", and its parameters can be learned using the "wake-sleep" method, in which learning of the primary "generative" model is assisted by a "recognition" model, whose role is to fill in the values of hidden variables based on the values of visible variables. The generative and recognition models are jointly learned in "wake" and "sleep" phases, using just the delta rule. This learning procedure is comparable in simplicity to Oja's version of Hebbian learning, which produces a somewhat different representation of correlations in terms of principal components. We argue that the simplicity of wake-sleep learning makes factor analysis a plausible alternative to Hebbian learning as a model of activity-dependent cortical plasticity. This technical report is available in compressed Postscript by ftp to the following URL: ftp://ftp.cs.toronto.edu/pub/radford/ws-fa.ps.Z ---------------------------------------------------------------------------- Radford M. Neal radford@cs.utoronto.ca Dept. of Statistics and Dept. of Computer Science radford@utstat.utoronto.ca University of Toronto http://www.cs.utoronto.ca/~radford ---------------------------------------------------------------------------- From john@dcs.rhbnc.ac.uk Thu Jul 25 21:55:54 1996 Received: from lucy.cs.wisc.edu (lucy.cs.wisc.edu [128.105.2.11]) by sea.cs.wisc.edu (8.6.12/8.6.12) with ESMTP id VAA25366 for ; Thu, 25 Jul 1996 21:55:05 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.6.12/8.6.12) with SMTP id VAA19843 for ; Thu, 25 Jul 1996 21:55:03 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa27608; 25 Jul 96 15:17:17 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa27605; 25 Jul 96 15:07:53 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa06146; 25 Jul 96 15:05:56 EDT Received: from EDRC.CMU.EDU by B.GP.CS.CMU.EDU id aa12547; 25 Jul 96 11:25:47 EDT Received: from dns1.rhbnc.ac.uk by EDRC.CMU.EDU id aa13405; 25 Jul 96 11:25:38 EDT Received: from localhost (localhost [127.0.0.1]) by platon.cs.rhbnc.ac.uk (8.6.9/8.6.9) with SMTP id QAA12702 ; Thu, 25 Jul 1996 16:17:06 +0100 From: John Shawe-Taylor Message-Id: <199607251517.QAA12702@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, vovk@dcs.rhbnc.ac.uk, alex@dcs.rhbnc.ac.uk, pete@dcs.rhbnc.ac.uk, dave@dcs.rhbnc.ac.uk, jon@dcs.rhbnc.ac.uk, anthony@vax.lse.ac.uk, Paul.Vitanyi@cwi.nl, Esko Ukkonen , orponen@igi.tu-graz.ac.at, Michel.Cosnard@lip.ens-lyon.fr, maass@igi.tu-graz.ac.at, cesabian@dsi.unimi.it, mauri , vigna@dsi.unimi.it, Felipe Cucker , chrmich@sun1.umh.ac.be, sbruyere@vm1.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, panizza@cse.ucsc.edu, ferretti@dsi.unimi.it, g.r.brightwell@lse.ac.uk, hpaugam@lip.ens-lyon.fr, mschmitt@igi.tu-graz.ac.at, boldi@dsi.unimi.it, Bernard.Girau@lip.ens-lyon.fr, Tapio.Elomaa@cs.Helsinki.FI, jkivinen@varisluoto.cs.Helsinki.FI, Petri.Myllymaki@cs.Helsinki.FI, koiran@lip.ens-lyon.fr, pauer@igi.tu-graz.ac.at, Didier.Puzenat@lip.ens-lyon.fr, Richard.Baron@lip.ens-lyon.fr, castro@lsi.upc.es, buhrman@cwi.nl, jeroenm@cwi.nl, david@goliat.upc.es, vlavin@lsi.upc.es, carlos@cs.titech.ac.jp, pdg@cwi.nl, N.L.Biggs@lse.ac.uk, Herman.Ehrenburg@cwi.nl, gegout@clipper.ens.fr, Olivier.Bournez@lip.ens-lyon.fr, gakwaya@sun1.umh.ac.be, simon@nereus.informatik.uni-dortmund.de, shai@csa.CS.Technion.AC.IL, bartlett@deakin.anu.edu.au, williams@faceng.anu.edu.au, colt@cs.uiuc.edu, Connectionists@cs.cmu.edu, enns-list@dcs.kcl.ac.uk, neur-sci@dl.ac.uk, comp-neuro@smaug.bbb.caltech.edu, neuron-request@cattell.psych.upenn.edu Subject: Technical Report Series in Neural and Computational Learning Date: Thu, 25 Jul 96 16:17:05 +0100 X-Mts: smtp The European Community ESPRIT Working Group in Neural and Computational Learning Theory (NeuroCOLT) has produced a set of new Technical Reports available from the remote ftp site described below. They cover topics in real valued complexity theory, computational learning theory, and analysis of the computational power of continuous neural networks. Abstracts are included for the titles. *** Please note that the location of the files was changed at the beginning of ** the year, so that any copies you have of the previous instructions should be * discarded. The new location and instructions are given at the end of the list. ---------------------------------------- NeuroCOLT Technical Report NC-TR-96-047: ---------------------------------------- A Graph-theoretic Generalization of the Sauer-Shelah Lemma by Nicol\`o Cesa-Bianchi, University of Milan, Italy David Haussler, University of California, Santa Cruz, USA Abstract: We show a natural graph-theoretic generalization of the Sauer-Shelah lemma. This result is applied to bound the $\ell_{\infty}$ and $L_1$ packing numbers of classes of functions whose range is an arbitrary, totally bounded metric space. ---------------------------------------- NeuroCOLT Technical Report NC-TR-96-048: ---------------------------------------- A Comparison between Cellular Encoding and Direct Encoding for Genetic Neural Networks by Fr\'ed\'eric Gruau, CWI, the Netherlands Darrell Whitley, Colorado State University, USA Abstract: This paper compares the efficiency of two encoding schemes for Artificial Neural Networks optimized by evolutionary algorithms. Direct Encoding encodes the weights for an a~priori fixed neural network architecture. Cellular Encoding encodes both weights and the architecture of the neural network. In previous studies, Direct Encoding and Cellular Encoding have been used to create neural networks for balancing 1 and 2 poles attached to a cart on a fixed track. The poles are balanced by a controller that push the cart to the left or the right. In some cases velocity information about the pole and cart is provided as an input; in other cases the network must learn to balance a single pole without velocity information. A careful study of the behavior of these systems suggests that it is possible to balance a single pole with velocity information as an input and without learning to compute the velocity. A new fitness function is introduced that forces ANN to compute the velocity. By using this new fitness function and tuning the syntactic constraints used with cellular encoding, we achieve a tenfold speedup over our previous study and solve a more difficult problem: balancing two poles when no information about the velocity is provided as input. -------------------------------------------------------------------- ***************** ACCESS INSTRUCTIONS ****************** The Report NC-TR-96-001 can be accessed and printed as follows % ftp ftp.dcs.rhbnc.ac.uk (134.219.96.1) Name: anonymous password: your full email address ftp> cd pub/neurocolt/tech_reports ftp> binary ftp> get nc-tr-96-001.ps.Z ftp> bye % zcat nc-tr-96-001.ps.Z | lpr -l Similarly for the other technical reports. Uncompressed versions of the postscript files have also been left for anyone not having an uncompress facility. In some cases there are two files available, for example, nc-tr-96-002-title.ps.Z nc-tr-96-002-body.ps.Z The first contains the title page while the second contains the body of the report. The single command, ftp> mget nc-tr-96-002* will prompt you for the files you require. 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/neural/neurocolt.html or directly to the archive: ftp://ftp.dcs.rhbnc.ac.uk/pub/neurocolt/tech_reports Best wishes John Shawe-Taylor From tanig@burton.zfe.siemens.de Fri Jul 26 13:39:33 1996 Received: from lucy.cs.wisc.edu (lucy.cs.wisc.edu [128.105.2.11]) by sea.cs.wisc.edu (8.6.12/8.6.12) with ESMTP id NAA11029 for ; Fri, 26 Jul 1996 13:39:24 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.6.12/8.6.12) with SMTP id NAA00508 for ; Fri, 26 Jul 1996 13:39:22 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa00792; 26 Jul 96 11:20:36 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa00790; 26 Jul 96 11:07:59 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa07080; 26 Jul 96 11:07:40 EDT Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa28902; 26 Jul 96 8:33:01 EDT Received: from david.siemens.de by CS.CMU.EDU id aa23357; 26 Jul 96 8:32:40 EDT Received: from ztivax.zfe.siemens.de (root@ztivax.siemens.de [146.254.1.2]) by david.siemens.de (8.7.5/8.7.3) with SMTP id OAA19401; Fri, 26 Jul 1996 14:27:42 +0200 (MDT) Received: from burton.zfe.siemens.de (burton) by ztivax.zfe.siemens.de with SMTP id AA25580 (5.67a/IDA-1.5); Fri, 26 Jul 1996 14:30:39 +0200 Received: (from tanig@localhost) by burton.zfe.siemens.de (8.6.12/8.6.12) id OAA29944; Fri, 26 Jul 1996 14:26:20 +0200 Date: Fri, 26 Jul 1996 14:26:20 +0200 From: Michiaki Taniguchi Message-Id: <199607261226.OAA29944@burton.zfe.siemens.de> To: colt@cs.uiuc.edu, Connectionists@cs.cmu.edu, enns-list@dcs.kcl.ac.uk, reinforce@cs.uwa.edu.au, neur-sci@dl.ac.uk Subject: NEuroNet Industrial Studentship X-Sun-Charset: ISO-8859-1 ************************************************************************ NEuroNet Industrial Studentship at the Neural Network Group, Siemens Corporate Research ************************************************************************ Two studentships in the amount of 800 ECU/month for six months are available from the NEuroNet program for EU students. A major objective of NEuroNet Industrial Studentship is to provide an opportunity for students to gain experience in the industrial environment. Siemens will provide supervision of two students for SIX months in the laboratory located in Munich/Germany. The students will be assigned to project-relevant tasks in the area of telecommunications. During this time the students will have an opportunity to become acquainted with real-world applications of Neural Networks in the industrial environment. Siemens is one of the largest companies in the electrical and electronics industry world-wide, with at present about 2000 staff members in its Corporate Research and Development Division. In the Neural Network Project, which was started in 1988, more than 20 scientists and about an equal number of graduate and Ph.D. students are working on the theory and on applications of Neural Networks, among others, in: - time-series forecasting - non-linear statistics and dynamics - non-linear modeling and control - development of simulation environment for Neural Networks - telecommunications One of the main areas of activity of Siemens is telecommunication - an area where we see promising new applications of Neural Networks. By now, Neural Networks are established as a new technology for modeling and control of complex technical systems. We see a large potential to improve the current technology of telecommunication by neural based approaches. Requirements: - programming experience (C, C++, Matlab,...) - basic knowledge in Neural Networks - capability of independent work - background in telecommunication would be desirable Applicants should send as soon as possible a cv (curriculum vitae) which states nationality, place of study, their research interests and, if available, a list of publications. They have to be registered for a university degree (undergraduate or graduate students). During the six months, the financial support by NEuroNet will be 800 ECU per month. Time-scale: The studentship should start autumn/winter this year and will last for 6 month. Applications should be send as soon as possible to: Michiaki Taniguchi Address: ZFE T SN 4, Siemens AG Otto-Hahn-Ring 6 D-81739 M|nchen, Germany Phone: +49/89/636-49506 Fax: +49/89/636-49767 e-mail: Michiaki.Taniguchi@zfe.siemens.de ------------------------------------------------------------------------------ _/ Michiaki Taniguchi Phone: +49/89/636-49506 _/ _/ _/ ZFE T SN 4 Fax: +49/89/636-49767 _/_/ _/ _/ _/ _/_/_/ Siemens AG _/ _/ _/ _/ _/ Otto-Hahn-Ring 6 _/ _/ _/ _/ _/_/_/ 81730 Muenchen Germany e-mail: Michiaki.Taniguchi@zfe.siemens.de http://www.siemens.de/zfe_nn/homepage.html From N.Sharkey@dcs.shef.ac.uk Fri Jul 26 13:39:43 1996 Received: from lucy.cs.wisc.edu (lucy.cs.wisc.edu [128.105.2.11]) by sea.cs.wisc.edu (8.6.12/8.6.12) with ESMTP id NAA11032 for ; Fri, 26 Jul 1996 13:39:28 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.6.12/8.6.12) with SMTP id NAA00513 for ; Fri, 26 Jul 1996 13:39:24 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa00830; 26 Jul 96 11:38:42 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa00795; 26 Jul 96 11:08:51 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa07086; 26 Jul 96 11:08:31 EDT Received: from EDRC.CMU.EDU by B.GP.CS.CMU.EDU id aa29288; 26 Jul 96 9:02:58 EDT Received: from gw.dcs.shef.ac.uk by EDRC.CMU.EDU id aa18339; 26 Jul 96 9:02:36 EDT Received: from freud.dcs.shef.ac.uk by dcs.shef.ac.uk (4.1/DAVE-1.0) id AA19506; Fri, 26 Jul 96 14:01:40 BST Date: Fri, 26 Jul 96 14:01:40 BST From: Noel Sharkey Message-Id: <9607261301.AA19506@dcs.shef.ac.uk> To: connect-bb@ed.eusip, incon@dcs.shef.ac.uk, reinforce@cs.uwa.edu.au, gann-list@cs.iastate.edu, neuron-request@CATTELL.psych.upenn.edu, alife@cognet.ucla.edu, cogpsy@neuro.psy.soton.ac.uk, connectionists@cs.cmu.edu, epsynet%uhupvm1.BITNET@cunyvm.cuny.edu, hybrid-list@cs.ua.edu, colt@cs.uiuc.edu Subject: ROBOT LEARNING: the new wave Cc: N.Sharkey@dcs.shef.ac.uk see FAQs below: ****** ROBOT LEARNING: THE NEW WAVE ****** Special Issue of Robotics and Autonomous Systems SPECIAL EDITOR Noel Sharkey (Sheffield) SPECIAL EDITORIAL BOARD Michael Arbib (USC) Ronald Arkin (GIT) George Bekey (USC) Randall Beer (Case Western) Bartlett Mel (USC) Maja Mataric (Brandeis) Carme Torras (Spain) Lina Massone (Northwestern) Lisa Meeden (Swarthmore) + large international REVIEW PANEL (see web page) A number of people have writing to me with questions regarding the special issue. I thought that it would be better to forward the answers to everyone. FAQs Q. Where can I get information about the issue and instructions to authors? A. The full call and link to instruction can be found at www.dcs.shef.ac.uk/research/groups/nn/RASspecial.html Q. I am nearly finished my paper but need an extension of the deadline? A. Since I shall be on vacation for two weeks, authors can have an extension of two weeks (15th August). Q. The call for papers stressed a bias in favour of papers reporting implementations on real robot. We have a paper that is based on a very relevant simulation (or a review), is that acceptable? A. Our main objective is to publish high quality papers that reflect the state of the art in robot learning. The bias (given papers of equal quality) WILL be for real implementations. However, we realise that there is other important research that bears directly on robot learning problems. We will accept submission of any such relevant papers. noel