From stefan.kremer@crc.doc.ca Tue Oct 1 18:52:59 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 SAA01579 for ; Tue, 1 Oct 1996 18:52:39 -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 NAA21854 for ; Tue, 1 Oct 1996 13:56:54 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa28401; 1 Oct 96 13:18:58 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa28399; 1 Oct 96 12:53:11 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa27663; 1 Oct 96 12:52:35 EDT Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa18267; 1 Oct 96 11:36:12 EDT Received: from [142.92.37.83] by CS.CMU.EDU id aa28735; 1 Oct 96 11:35:21 EDT Received: from broadreach (broadreach.dgcd.doc.ca) by digame (4.1/SMI-4.1) id AA00839; Tue, 1 Oct 96 11:32:58 EDT Message-Id: <2.2.32.19961001153248.00696364@digame.dgcd.doc.ca> X-Sender: kremer@digame.dgcd.doc.ca X-Mailer: Windows Eudora Pro Version 2.2 (32) Mime-Version: 1.0 Content-Type: text/plain; charset="us-ascii" Date: Tue, 01 Oct 1996 11:32:48 -0400 To: connectionists@cs.cmu.edu From: "Stefan C. Kremer" Subject: Ph.D. dissertation available: A Theory of Grammatical Induction in the Connectionist Paradigm FTP-host: archive.cis.ohio-state.edu FTP-filename: /pub/neuroprose/filename.ps.Z **DO NOT FORWARD TO OTHER GROUPS** Greetings Connectionists Readers: My Ph.D. Dissertation, entitled "A Theory of Grammatical Induction in the Connectionist Paradigm" is now available for anonymous FTP from the Neuroprose archive. Details are provided below. -Stefan ======================================================== A Theory of Grammatical Induction in the Connectionist Paradigm Abstract This dissertation shows that the tractability and efficiency of training particular connectionist networks to implement certain classes of grammars can be formally determined by applying principles and ideas that have been explored in the symbolic grammatical induction paradigm. Furthermore, this formal analysis also allows networks to be tailored to efficiently solve specific grammatical induction problems. Had the formal work that is reported in this dissertation been done earlier, it is possible that connectionist researchers would have been able to take a formal, rather than empirical, approach to understanding the computational power of their nets for grammatical induction. As well, our formal approach could have been applied to understand and develop techniques to functionally increase the power of connectionist grammar induction systems. Instead, these techniques are currently being discovered empirically. This dissertation, by considering classical work done over the past three decades, gives a formal grounding to these empirically discovered methods. In doing so, it also suggests a rationale for making the design decisions which define every connectionist grammar induction system. This allows new networks to be better suited to the problems to which they will be applied. Finally, the dissertation provides insights into applying other refinement techniques that connectionist researchers have yet to consider. Distribution This document is distributed in the form of a tape archive file named: kremer.thesis.tar.Z. The archive contains 7 individual Postscript files named: "kremer.thesis1.ps" (14 pages), "kremer.thesis2.ps" (33 pages), "kremer.thesis3.ps" (12 pages), "kremer.thesis4.ps" (28 pages), "kremer.thesis5.ps" (8 pages), "kremer.thesis6.ps" (33 pages), and "kremer.thesis7.ps" (10 pages). The first file (thesis1) contains the titlepage, copyright notice, abstract, table of contents, list of tables, list of figures, list of abbreviations, list of symbols and introductory chapter of the dissertation. It may help you to decide which sections of the manuscript you wish to download or print. The last file (thesis7) contains both the concluding chapter and the bibliography for the entire document, while all other files each contain the chapter corresponding to their number (i.e. thesis2 contains Chapter 2). At the present time the f ile "kremer.thesis.tar.Z" is available via anonymous FTP from the Neuroprose Archive at URL "ftp://archive.cis.ohio-state.edu/pub/neuroprose/thesis/kremer.thesis.tar.Z" , however, the author reserves the right to remove the file at any time without prior notice. Sorry, the author cannot supply hardcopy versions of this document. Transcript Showing Access Procedure Here is a transcript showing the procedure to retrieve, "de-archive", uncompress, and print the dissertation. This works on my UNIX system. Success with other systems may vary: <*** BEGIN TRANSCRIPT ***> > >ftp archive.cis.ohio-state.edu Connected to archive.cis.ohio-state.edu. 220 archive FTP server (Version wu-2.4(1) Wed Jul 5 14:19:42 EDT 1995) ready. Name (archive.cis.ohio-state.edu:kremer): anonymous 331 Guest login ok, send your complete e-mail address as password. Password: 230 Guest login ok, access restrictions apply. ftp> cd pub/neuroprose/Thesis 250 CWD command successful. ftp> binary 200 Type set to I. ftp> get kremer.thesis.tar.Z 200 PORT command successful. 150 Opening BINARY mode data connection for kremer.thesis.tar.Z (2265663 bytes). 226 Transfer complete. local: kremer.thesis.tar.Z remote: kremer.thesis.tar.Z 2265663 bytes received in 1.2e+02 seconds (18 Kbytes/s) ftp> bye 221 Goodbye. >uncompress kremer.thesis.tar.Z >tar xvf kremer.thesis.tar x kremer.thesis1.ps, 229167 bytes, 448 tape blocks x kremer.thesis2.ps, 2324747 bytes, 4541 tape blocks x kremer.thesis3.ps, 315922 bytes, 618 tape blocks x kremer.thesis4.ps, 2746246 bytes, 5364 tape blocks x kremer.thesis5.ps, 269211 bytes, 526 tape blocks x kremer.thesis6.ps, 2422155 bytes, 4731 tape blocks x kremer.thesis7.ps, 114407 bytes, 224 tape blocks >lpr -s kremer.thesis?.ps <*** END TRANSCRIPT ***> Comments and Corrections If you have any comments or corrections for the author, please e-mail them to: stefan.kremer@crc.doc.ca. -- Dr. Stefan C. Kremer, Neural Network Research Scientist, Communications Research Centre, 3701 Carling Ave., P.O. Box 11490, Station H, Ottawa, Ontario K2H 8S2 WWW: http://running.dgcd.doc.ca/~kremer/index.html Tel: (613)990-8175 Fax: (613)990-8369 E-mail: Stefan.Kremer@crc.doc.ca From freeman@systems.caltech.edu Wed Oct 2 06:36:43 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 GAA20543 for ; Wed, 2 Oct 1996 06:36:39 -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 GAA04889 for ; Wed, 2 Oct 1996 06:36:33 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa29418; 2 Oct 96 4:49:55 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa29416; 2 Oct 96 4:37:52 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa28407; 2 Oct 96 4:37:26 EDT Received: from EDRC.CMU.EDU by B.GP.CS.CMU.EDU id aa04316; 2 Oct 96 3:24:12 EDT Received: from gladstone.systems.caltech.edu by EDRC.CMU.EDU id aa28247; 2 Oct 96 3:23:40 EDT Received: by gladstone.systems.caltech.edu (4.1/1.34.1) id AA18979; Wed, 2 Oct 96 00:20:31 PDT Date: Wed, 2 Oct 96 00:20:31 PDT From: Robert Freeman Message-Id: <9610020720.AA18979@gladstone.systems.caltech.edu> To: addistr@sis.port.ac.uk Subject: Conference: Nerual Networks in the Capital Markets 11/20/96 ******************************************************************************* --- Registration Package and Preliminary Program --- NNCM-96 FOURTH INTERNATIONAL CONFERENCE NEURAL NETWORKS IN THE CAPITAL MARKETS Wednesday-Friday, November 20-22, 1996 The Ritz-Carlton Hotel, Pasadena, California, U.S.A. Sponsored by Caltech and London Business School http://cs.caltech.edu/~learn/nncm Neural networks have been applied to a number of live systems in the capital markets, and in many cases have demonstrated better performance than competing approaches. Because of the increasing interest in the NNCM conferences held in the U.K. and the U.S., the fourth annual NNCM will be held on November 20-22, 1996, in Pasadena, California. This is a research meeting where original and significant contributions to the field are presented. A day of tutorials (Wednesday, November 20) is included to familiarize audiences of different backgrounds with some of the key financial and mathematical aspects of the field. Invited Speakers: The conference will feature invited talks by three internationally recognized researchers: Dr. Rob Engle, UC San Diego Dr. Andrew Lo, MIT Sloan School Dr. Paul Refenes, London Business School Contributed Papers: NNCM-96 will have 4 oral sessions and 2 poster sessions with more than 40 contributed papers presented by academicians and practitioners from all six continents, both from the neural networks side and the capital markets side. Each paper has been refereed by 3 experts in the field. The areas of the accepted papers include price forecasting for stocks, bonds, commodities, and foreign exchange; asset allocation and risk management; volatility analysis and pricing of derivatives; cointegration, correlation, and multivariate data analysis; credit assessment and economic forecasting; statistical methods, learning techniques, and hybrid systems. Tutorials: Before the main program, there will be a day of tutorials on Wednesday, November 20, 1996. Three two-hour tutorials will be presented as follows: Statistical Models of Financial Volatility Dr. Rob Engle, University of California, San Diego Universal Portfolios and Information Theory Dr. Tom Cover, Stanford University Data-Snooping and Other Selection Biases in Financial Econometrics Dr. Andrew Lo, MIT Sloan School We are very pleased to have tutors of such caliber help bring new audiences from different backgrounds up to speed in this cross-disciplinary area. Schedule Outline: Wednesday, November 20: 9:00- 5:30 Tutorials 1, 2, 3 Thursday, November 21: 8:30-11:30 Oral Session I 11:30- 2:00 Luncheon & Poster Session I 2:00- 5:00 Oral Session II Friday, November 22: 8:30-11:30 Oral Session III 11:30- 2:00 Luncheon & Poster Session II 2:00- 5:00 Oral Session IV Organizing Committee: Dr. Y. Abu-Mostafa, Caltech (Chairman) Dr. A. Atiya, Cairo University Dr. N. Biggs, London School of Economics Dr. D. Bunn, London Business School Dr. M. Jabri, Sydney University Dr. B. LeBaron, University of Wisconsin Dr. A. Lo, MIT Sloan School Dr. I. Matsuba, Chiba University Dr. J. Moody, Oregon Graduate Institute Dr. C. Pedreira, Catholic Univ. PUC-Rio Dr. A. Refenes, London Business School Dr. M. Steiner, Universitaet Augsburg Dr. A. Timmermann, UC San Diego Dr. A. Weigend, University of Colorado Dr. H. White, UC San Diego Dr. L. Xu, Chinese University of Hong Kong Location: The conference will be held at the Ritz-Carlton Huntington Hotel in Pasadena, within two miles from the Caltech campus. One of the most beautiful hotels in the U.S., the Ritz is a 35-minute drive from Los Angeles International Airport (LAX) with nonstop flights from most major cities in North America, Europe, the Far East, Australia, and South America. Home of Caltech, Pasadena has recently become a major dining/hangout center for Southern California with the growth of its `Old Town', built along the styles of the 1950's. Among the cultural attractions of Pasadena are the Norton Simon Museum, the Huntington Library/Gallery/Gardens, and a number of theaters including the Ambassador Theater. Hotel Reservation: Please contact the Ritz-Carlton Huntington Hotel in Pasadena directly. The phone number is (818) 568-3900 and the fax number is (818) 568-1842. Ask for the NNCM-96 rate. We have negotiated an (incredible) rate of $79+taxes ($110 with $31 credited by NNCM-96 upon registration) per room (single or double occupancy) per night. Please make the hotel reservation IMMEDIATELY as the rate is based on availability. Registration: Registration is done by mail on a first-come, first-served basis. To ensure your place at the conference, please send the following registration form and payment as soon as possible to Ms. Lucinda Acosta, Caltech 136-93, Pasadena, CA 91125, U.S.A. Please make check payable to Caltech. - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - NNCM-96 Registration Form Title:------ Name:------------------------------------------------ Mailing address:------------------------------------------------ ------------------------------------------------ ------------------------------------------------ ------------------------------------------------ e-mail:--------------------------------- fax:--------------------------------- ********Please circle the applicable fees and write the total below******** Main Conference (November 21-22): Registration fee $550 Discounted fee for academicians $275 (letter on university letterhead required) Discounted fee for full-time students $150 (letter from registrar or faculty advisor required) Tutorials (November 20): You must be registered for the main conference in order to register for the tutorials. Tutorials Fee $150 Full-time students $100 (letter from registrar or faculty advisor required) TOTAL: $_________ Please include payment (check or money order in US currency). Please make check payable to Caltech. Mail your completed registration form and payment to Ms. Lucinda Acosta, Caltech 136-93, Pasadena, CA 91125, U.S.A. - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Transportation: There is shuttle service (around $25 per person) and bus service (around $15 per person) from Los Angeles International Airport (LAX) to the Ritz-Carlton Hotel in Pasadena. A taxi ride will cost approximately $55. There is also shuttle service from Burbank airport (BUR) which is a domestic airport closer to Pasadena. A taxi ride will cost approximately $35. Secretariat: For further information, please contact the NNCM-96 secretariat: Ms. Lucinda Acosta, Caltech 136-93, Pasadena, CA 91125, U.S.A. e-mail: lucinda@sunoptics.caltech.edu phone (818) 395-4843, fax (818) 795-0326 ******************************************************************************* From wyler@iam.unibe.ch Wed Oct 2 18:41:58 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 SAA03791 for ; Wed, 2 Oct 1996 18:41:53 -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 SAA17916 for ; Wed, 2 Oct 1996 18:41:51 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa29513; 2 Oct 96 6:40:46 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa29511; 2 Oct 96 6:33:31 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa28594; 2 Oct 96 6:32:58 EDT Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa07150; 2 Oct 96 6:25:26 EDT Received: from arwen.unibe.ch by CS.CMU.EDU id aa07456; 2 Oct 96 6:24:24 EDT Date: Wed, 2 Oct 1996 12:20:18 +0200 From: Kuno Wyler Message-Id: <9610021020.AA11589@garfield.unibe.ch> To: connectionists@cs.cmu.edu Subject: POSTDOCTORAL RESEARCH FELLOWSHIP X-Sun-Charset: US-ASCII POSTDOCTORAL RESEARCH FELLOWSHIP -------------------------------- Neural Computing Research Group Institute of Informatics and Applied Mathematics University of Bern, Switzerland The Neural Computing Research Group at the University of Bern is looking for a highly motivated individual for a two year postdoctoral research position in the area of development of a neuromorphic perception system based on multi sensor fusion. The aim of the project is to develop a neurobiologically plausible perception system for novelty detection in a real world environment (e.g. quality control in industrial production lines or supervision of security zones) based on information from different sensor channels and fast learning algorithms. Potential candidates should have strong mathematical and signal processing skills, with a background in neurobiology and neural networks. Working knowledge of programming (Matlab, LabView or C/C++) or VLSI technology is highly desirable but not required. The position will begin January 1, 1997, with possible renewal for an additional two years. The initial salary is SFr. 60'000/year (approx. $50'000). To apply for this position, send your curriculum vitae, publication list with one or two sample publications and two letters of reference before November 1, 1996, either by e-mail or surface mail to wyler@iam.unibe.ch or Dr. Kuno Wyler Neural Computing Research Group Institute of Informatics and Applied Mathematics University of Bern Neubrueckstrasse 10 CH-3012 Bern Switzerland From ted@SPENCER.CTAN.YALE.EDU Wed Oct 2 23:19:06 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 XAA06696 for ; Wed, 2 Oct 1996 23:19:00 -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 XAA21764 for ; Wed, 2 Oct 1996 23:18:57 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa29896; 2 Oct 96 14:40:35 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa29894; 2 Oct 96 14:20:13 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa28885; 2 Oct 96 14:19:45 EDT Received: from RI.CMU.EDU by B.GP.CS.CMU.EDU id aa15068; 2 Oct 96 14:02:54 EDT Received: from SPENCER.CTAN.YALE.EDU by RI.CMU.EDU id aa26478; 2 Oct 96 14:02:32 EDT Received: from PLANCK.CTAN.YALE.EDU by SPENCER.CTAN.YALE.EDU via ESMTP; Wed, 2 Oct 1996 18:02:25 GMT Received: by PLANCK.CTAN.YALE.EDU (Sendmail-8.7.1/res.nnc.client.cf-3.6) id SAA00877; Wed, 2 Oct 1996 18:02:23 GMT Date: Wed, 2 Oct 1996 18:02:23 GMT From: ted@SPENCER.CTAN.YALE.EDU Message-Id: <199610021802.SAA00877@PLANCK.CTAN.YALE.EDU> To: connectionists@cs.cmu.edu CC: ted@SPENCER.CTAN.YALE.EDU Subject: Relating neuronal form to function A digital preprint, issued somewhat belatedly-- at http://www.nnc.yale.edu/papers/NIPS94/nipsfin.html, the html version of our final draft of this paper: Carnevale, N.T., Tsai, K.Y., Claiborne, B.J., and Brown, T.H. The electrotonic transformation: a tool for relating neuronal form to function. In: Advances in Neural Information Processing Systems, vol. 7, edited by Tesauro, G., Touretzky, D.S., and Leen, T.K. Cambridge, MA, MIT Press, 1995, p. 69-76. Roughly 64K total, including figures. ABSTRACT The spatial distribution and time course of electrical signals in neurons have important theoretical and practical consequences. Because it is difficult to infer how neuronal form affects electrical signaling, we have developed a quantitative yet intuitive approach to the analysis of electrotonus. This approach transforms the architecture of the cell from anatomical to electrotonic space, using the logarithm of voltage attenuation as the distance metric. We describe the theory behind this approach and illustrate its use. --Ted From kak@ee.lsu.edu Thu Oct 3 05:54:07 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 FAA08515 for ; Thu, 3 Oct 1996 05:54:01 -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 FAA24753 for ; Thu, 3 Oct 1996 05:53:59 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa00373; 2 Oct 96 19:16:32 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa00371; 2 Oct 96 19:05:54 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa29086; 2 Oct 96 19:05:36 EDT Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa16972; 2 Oct 96 15:22:10 EDT Received: from gate.ee.lsu.edu by CS.CMU.EDU id aa12058; 2 Oct 96 15:21:29 EDT Received: by ee.lsu.edu (4.1/SMI-4.1) id AA05823; Wed, 2 Oct 96 14:21:25 CDT Date: Wed, 2 Oct 96 14:21:25 CDT From: Subhash Kak Message-Id: <9610021921.AA05823@ee.lsu.edu> To: connectionists@cs.cmu.edu The following papers may be retrieved by anonymous ftp: 1. Speed of Computation and Simulation by S.C. Kak ftp://gate.ee.lsu.edu/pub/kak/spee.ps.Z Abstract: This paper reviews several issues related to information, speed of computation, and simulation of a physical process. It is argued that mental processes proceed at a rate close to the optimal based on thermodynamic considerations. Problems related to the simulation of a quantum mechanical system on a computer are reviewed. Parallels are drawn between biological and adaptive quantum systems. Just published in *Foundations of Physics*, vol 26, 1375-1386, 1996 2. Can we define levels of artificial intelligence? by S.C. Kak Abstract: This paper argues for a graded approach to the study of machine intelligence. In contrast to the Turing Test approach, such an approach has the potential of defining incremental progress in machine intelligence research. Just published in *Journal of Intelligent Systems*, vol 6, 133-144, 1996 ftp://gate.ee.lsu.edu/pub/kak/ai.ps.Z From jhf@playfair.Stanford.EDU Thu Oct 3 20:12:24 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 UAA17942 for ; Thu, 3 Oct 1996 20:12:14 -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 UAA06494 for ; Thu, 3 Oct 1996 20:12:11 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa01930; 3 Oct 96 19:18:12 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa01928; 3 Oct 96 18:57:09 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa00196; 3 Oct 96 18:56:58 EDT Received: from RI.CMU.EDU by B.GP.CS.CMU.EDU id aa10433; 3 Oct 96 14:21:46 EDT Received: from Playfair.Stanford.EDU by RI.CMU.EDU id aa02950; 3 Oct 96 14:21:07 EDT Received: (from jhf@localhost) by playfair.Stanford.EDU (8.7.1/8.6.10) id LAA26129 for Connectionists@cs.cmu.edu; Thu, 3 Oct 1996 11:21:04 -0700 Date: Thu, 3 Oct 1996 11:21:04 -0700 From: "Jerome H. Friedman" Message-Id: <199610031821.LAA26129@playfair.Stanford.EDU> To: Connectionists@cs.cmu.edu Subject: TR available: Polychotomous classification. *** Technical Report available *** ANOTHER APPROACH TO POLYCHOTOMOUS CLASSIFICATION Jerome H. Friedman Stanford University (jhf@stat.stanford.edu) ABSTRACT An alternative solution to the K - class (K > 2 - polychotomous) classific- ation problem is proposed. It is a simple extension of K = 2 (dichotomous) classification in that a separate two-class decision boundary is independently constructed between every pair of the K classes. Each of these boundaries is then used to assign an unknown observation to one of its two respective classes. The individual class that receives the most such assignments over these K(K-1)/2 decisions is taken as the predicted class for the observation. Motivation for this approach is provided along with discussion as to those situations where it might be expected to do better than more traditional methods. Examples are presented illustrating that substantial gains in accuracy can sometimes be achieved. Available by ftp from: "ftp://stat.stanford.edu/pub/friedman/poly.ps.Z" Note: this postscript does not view properly on some ghostviews. It does seem to print properly on nearly all postscript printers. From gaudiano@cns.bu.edu Fri Oct 4 01:35:38 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 BAA20356 for ; Fri, 4 Oct 1996 01:35:33 -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 BAA09544 for ; Fri, 4 Oct 1996 01:35:25 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa01939; 3 Oct 96 19:27:40 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa01932; 3 Oct 96 18:58:08 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa00203; 3 Oct 96 18:57:06 EDT Received: from EDRC.CMU.EDU by B.GP.CS.CMU.EDU id aa14896; 3 Oct 96 18:14:42 EDT Received: from CNS.BU.EDU by EDRC.CMU.EDU id aa08654; 3 Oct 96 18:14:00 EDT Received: from ruggles.bu.edu by cns.bu.edu (SMI-8.6/BU-11/2/94) id SAA11219; Thu, 3 Oct 1996 18:03:55 -0400 From: Paolo Gaudiano Received: by ruggles.bu.edu (8.7.5/BU-941102) id SAA24959; Thu, 3 Oct 1996 18:03:56 -0400 (EDT) Date: Thu, 3 Oct 1996 18:03:56 -0400 (EDT) Message-Id: <199610032203.SAA24959@ruggles.bu.edu> To: connectionists@cs.cmu.edu Subject: IMPORTANT: WCNN'97 has merged with ICNN'97 IMPORTANT ANNOUNCEMENT for INNS Members and others who planned to submit papers to the World Congress on Neural Networks (WCNN97). From the Board of Governors of the International Neural Network Society The INNS Board of Governors urges all INNS members and other potential authors to speed up preparation of their technical papers to meet a November 15, 1996, deadline (instead of the previously announced date of January 15, 1997). There will be only one major US neural network meeting in 1997: Houston, June 9-12, 1997 The INNS Board of Governors took a positive and definite step toward reinstituting the tradition of joint neural network meetings with the IEEE. Specifically, it was decided to replace the planned 1997 INNS meeting in Boston by offering strong technical involvement in the Houston meeting being planned by the IEEE, June 9-12, 1997. The IEEE has accepted the offer. INNS will be listed as a Technical Co-Sponsor of the meeting, and IEEE has invited the INNS Program Chair, Dan Levine, to serve as a Program Co-Chair for their meeting. The chairs are working together to develop sessions and/or tracks to accommodate certain addtional technical areas traditionally of interest to INNS members. A copy of the IEEE Call for Papers for the 1997 ICNN in Houston is attached. Please note that the paper submission deadline listed is November 1, 1997. Due to the shortness of time, IEEE is willing to allow up to two weeks grace period for INNS members. Thus, November 15th is to be seen as an "absolute" deadline. Additional information can be found on the IEEE ICNN web site at: http://www.mindspring.com/~pci-inc/ICNN97 We look forward to seeing all of you in Houston. ---------------------------------------------------------------------- WELCOME TO THE BRAND NEW ICNN'97 CALL FOR PAPERS..... IEEE-NNC and INNS, in the spirit of earlier IJCNN's, Co-sponsor ICNN97 and Future Conferences ... /////////////////////////////////////////// / / / I C N N ' 9 7 / / / /////////////////////////////////////////// New ICNN '97 Call for Papers INTERNATIONAL CONFERENCE ON NEURAL NETWORKS (ICNN'97) Westin Galleria Hotel, Houston, Texas, USA Tutorials June 8, Conference June 9-12, 1997 CO-SPONSORED BY THE IEEE NEURAL NETWORKS COUNCIL AND THE INTERNATIONAL NEURAL NETWORKS SOCIETY NNC....... IEEE....... INNS This conference is a major international forum for researchers, practitioners and policy makers interested in natural and artificial neural networks. Submissions of papers related, but not limited, to the topics listed below are invited. Applications Architectures Associative Memory Cellular Neural Networks Computational Intelligence Cognitive Science Data Analysis Fuzzy Neural Systems Genetic and Annealing Algorithms Hardware Implementation (Electronic and Optical) Hybrid Systems Image and Signal Processing Intelligent Control Learning and Memory Machine Vision Model Identification Motion Vision Motion Analysis Neurobiology Neurocognition Neurosensors and Wavelets Neurodynamics and Chaos Optimization Pattern Recognition Prediction Robotics Sensation and Perception Sensorimotor Systems Speech, Hearing, and Language System Identification Supervised/Unsupervised Learning Time Series Analysis PAPER SUBMISSION: Papers must be received by the Technical Program Co-Chairs by November 1, 1996. PAPER DEADLINE NOV. 15 ### INNS MEMBERS ONLY ### Papers received after that date will be returned unopened. International authors should submit their work via Air Mail or Express Courier so as to ensure timely delivery. All submissions will be acknowledged by electronic or postal mail. Mail all papers to Prof. James M. Keller, Computer Engineering and Computer Science Department; 217 Engineering Building West; University of Missouri; Columbia, MO 65211 USA. Phone: (573) 882-7339. CONTACT General Chair, Prof. Nicolaos B. Karayiannis, at Karayiannis@UH.EDU; Program Co-Chairs: Prof. Daniel S. Levine , at b344dsl@utarlg.uta.edu ; Prof. Keller, at keller@ece.missouri.edu ; Prof. Raghu Krishnapuram, at raghu@ece.missouri.edu or other members of the Program Committee with questions. Six copies (one original and five copies) of the paper must be submitted. Papers must be camera-ready on 8 1/2 by 11 white paper, one-column format in Times or similar font style, 10 points or larger with one inch margins on all four sides. Do not fold or staple the original camera-ready copy. Four pages are encouraged; however, the paper must not exceed six pages, including figures, tables, and references, and should be written in English. Submissions that do not adhere to the guidelines above will be returned unreviewed. Centered at the top of the first page should be the complete title, author name(s), and postal and electronic mailing addresses. In the accompanying letter, the following information must be included: Full Title of the Paper Technical Area (First and Second Choices) Corresponding Author (Name, Postal and E-Mail Addresses, Telephone & FAX Numbers) Preferred Mode of Presentation (Oral or Poster) PAPER REVIEW: Papers will be reviewed by senior researchers in the field and authors will be informed of the decisions by January 2, 1997. Authors of accepted papers will be allowed to revise their papers, and the final versions must be received by February 1, 1997. BEST STUDENT PAPER AWARDS: To qualify, a student or group of students must contribute over 70% of the paper and be the PRIMARY AUTHORS(S). The submission should clearly indicate that the paper is to be considered for the best student paper award, the amount of contribution by the student, current level of study, and e-mail address. SPECIAL SESSIONS: Proposals for plenary and panel sessions must be submitted to the Plenary/Special Sessions Chair , Jacek Zurada by October 15, 1996. TUTORIALS: Proposals for tutorials must be submitted to the Tutorials Chair , John Yen, by October 15, 1996. EXHIBITOR INFORMATION: A large group of vendors and participants from industry, academia and government are expected. Potential exhibitors may request information from the Exhibits Chair, Joydeep Ghosh.. //////////////////// CONTACTS: //////////////////// TECHNICAL: For technical information on the conference, please contact members of the Organizing Committee REGISTRATION: Conference Secretariat: Meeting Management, 2603 Main Street, #690, Irvine, CA 92714 Phone: (714) 752-8205 Fax: (714) 752-7444 Email: Meeting Mgt@aol.com WEB-SITE: New Web Site: http://www.mindspring.com/~pci-inc/ICNN97 (Mary Lou Padgett) Original Web Sites: (Bogdan M. Wilamowski e-mail wilam@uwyo.edu.) Comments/questions on new ICNN'97: General Chair, Nicolaos B. Karayiannis Email: Karayiannis@UH.EDU INNS Board of Governors Member: Daniel S. Levine Email:b344dsl@utarlg.uta.edu /////////////////////////////////////////////////////// NEW ICNN'97 Members of the Organizing Committee /////////////////////////////////////////////////////// General Chair Prof. Nicolaos B. Karayiannis Dept. of Electrical & Computer Engineering University of Houston Houston TX 77204-4793, USA Phone: (713) 743-4436 Fax: (713) 743-4444 Email: Karayiannis@UH.EDU Technical Program and Proceedings Co-Chairs Prof. James M. Keller Computer Engineering and Computer Science Department 217 Engineering Building West University of Missouri Columbia, MO 65211 USA Phone: (573) 882-7339 Fax: (573) 882-0397 Email: keller@ece.missouri.edu Prof. Raghu Krishnapuram University of Missouri Computer Engineering and Computer Science Department Columbia MO 65211 USA Phone: (573) 882-7766 Fax: (573) 882-0397 Email: raghu@ece.missouri.edu INNS CONTACT: Prof. Daniel S. Levine Univ. of Texas at Arlington Department of Psychology Arlington, TX 76019-0408 Phone 817-272-3598 Fax 817-272-2364 Email: b344dsl@utarlg.uta.edu Tutorials Chair Prof. John Yen Texas A&M University Dept. of Computer Science 301 Harvey R. Bright Bldg. College Station TX 77843-3112 USA Phone: (409) 845-5466 Fax: (409) 847-8578 Email: yen@cs.tamu.edu Publicity Chair Mary Lou Padgett Auburn University or Padgett Computer Innovations, Inc. (PCI-INC) 1165 Owens Road Auburn AL 36830 US Phone: (334) 821-2472 Fax: (334) 821-3488 Email: m.padgett@ieee.org Exhibits Chair Prof. Joydeep Ghosh University of Texas Dept. of Electrical & Computer Engineering Engineering Sciences Building (ENS) 516 Austin TX 78712-1084 USA Phone: (512) 471-8980 Fax: (512) 471-5907 Email: ghosh@ece.utexas.edu Plenary/Special Sessions Chair Prof. Jacek M. Zurada University of Louisville Dept. of Electrical Engineering Louisville KY 40292 USA Phone: (502) 852-6314 Fax: (502) 852-6807 Email: jmzura02@starbase.spd.louisville.edu International Liaison Chair Prof. Sankar K. Pal Machine Intelligence Unit Indian Statistical Institute 203 B. T. Road Calcutta 700 035 INDIA Phone: (0091)-33-556-8085 Fax: (0091)-33-556-6925 Fax: (0091)-33-556-6680 Email: sankar@isical.ernet.in Finance Chair Prof. Ben H. Jansen University of Houston Dept. of Electrical & Computer Engineering Houston TX 77204-4793 USA Phone: (713) 743-4431 Fax: (713) 743-4444 Email: bjansen@uh.edu Local Arrangements Chair Prof. Heidar A. Malki University of Houston Electrical-Electronics Department Houston TX 77204-4083 USA Phone: (713) 743-4075 Fax: (713) 743-4032 Email: malki@uh.edu ////////////////////////////////////////////////////// ICNN'97 TUTORIAL SUBMISSIONS ////////////////////////////////////////////////////// ICNN 97 Tutorial Proposal Submission Guideline Tutorial proposals for 1997 IEEE International Conference on Neural Networks (ICNN 97) are solicited. The proposal should be prepared using the format described below. Proposal Format The proposal should contain the following information: Title and expected duration of the tutorial Objective and expected benefit of the tutorial participants Target audience and their required background A one paragraph justification about the timing of the tutorial. A topic that is in its infancy or is too mature is not likely to be suitable. Therefor, the timing of the proposed tutorial should be justified in terms of (1) the amount of interest in its subject area and (2) the current body of knowledge developed in the area. An outline of the material to be covered by the tutorial. Qualification and contact information (including e-mail address and FAX number) of the instructor Submission Information The proposal should be submitted to the Tutorial Chair of ICNN 97 at the following address by October 15, 1996 using postal mail or e-mail. Tutorial Chair Prof. John Yen Center for Fuzzy Logic, Robotics, and Intelligent Systems Department of Computer Science 301 Harvey R. Bright Bldg. Texas A&M University College Station, TX 77843-3112 U.S.A. TEL: (409) 845-5466 FAX: (409) 847-8578 E-mail: yen@cs.tamu.edu --===================== Mary Lou Padgett 1165 Owens Road Auburn, AL 36830 P: (334) 821-2472 F: (334) 821-3488 m.padgett@ieee.org Auburn University, EE Dept. Padgett Computer Innovations, Inc. (PCI) Simulation, VI, Seminars IEEE Standards Board -- Virtual Intelligence ( VI): NN, FZ, EC, VR --===================== From jung@service1.uky.edu Sat Oct 5 02:37:28 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 CAA05496 for ; Sat, 5 Oct 1996 02:37:19 -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 CAA24859 for ; Sat, 5 Oct 1996 02:37:14 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id ac03384; 5 Oct 96 1:17:37 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id ac03381; 5 Oct 96 0:54:54 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa01793; 5 Oct 96 0:54:37 EDT Received: from RI.CMU.EDU by B.GP.CS.CMU.EDU id aa07637; 4 Oct 96 17:14:19 EDT Received: from service1.cc.uky.edu by RI.CMU.EDU id aa10413; 4 Oct 96 17:13:23 EDT Received: from [] ([128.163.176.21]) by service1.cc.uky.edu (8.7.Beta.13/8.7.Beta.13) with SMTP id RAA24134; Fri, 4 Oct 1996 17:11:14 -0400 (EDT) Message-Id: <199610042111.RAA24134@service1.cc.uky.edu> Sender: jung@service1.uky.edu MMDF-Warning: Parse error in original version of preceding line at DST.BOLTZ.CS.CMU.EDU From: "Dr. Ranu Jung" To: bmes@mecca.mecca.org Date: Fri, 4 Oct 1996 16:03:24 +0000 Subject: Graduate Res. Asstantship Reply-to: jung@service1.uky.edu CC: cneuro@bbb.caltech.edu, connectionists@cs.cmu.edu, doll@magnum.cog.brown.edu, dmohan@cbme.iitd.ernet.in Priority: normal X-mailer: Pegasus Mail/Windows (v1.22) DYNAMICAL ANALYSIS OF LOCOMOTOR CONTROL (Graduate Research Assistantship) This position is part of a project funded by The Whitaker Foundation that is directed at examining the dynamical interaction between the brain and the spinal cord in the control of locomotion. The project involves experimental and computational studies with sub-projects for: 1) characterization of the intrinsic variability in the fictive locomotor rhythm obtained in in vitro brain-spinal cord preparations of the lamprey, 2) investigation of the role of the feedforward-feedback loop between the brain and the spinal cord in short- and long term control of locomotion (changes in stability states, responses to perturbations), and 3) mathematical model development (biophysically motivated neural networks for the central pattern generator for swimming) and analysis of the models using techniques from dynamical systems theory. The analysis of experimental data will include development of novel signal processing methods and use of techniques from nonlinear systems analysis. The project will be conducted at the Experimental and Computational Neuroscience Laboratory at the Center for Biomedical Engineering. In additin to ties within the Center the laboratory collaborates with members of the Department of Electrical Engineering and the Department of Physiology. The position is available for up to three years for graduate work. Applications, including CV and names of two references, may be sent to Dr. Ranu Jung by email(jung@pop.uky.edu), by FAX(606-257-1856) , or by postal mail to Ranu Jung, Ph.D. 21 Wenner Gren Research Laboratory University of Kentucky Lexington, KY 40506-0070. Additional information can be obtained by contacting Dr. Jung by email or telephone (606-257-5931). Information about other neuroscience related research being conducted at the Center can be obtained from the web at the URL http://www.uky.edu/RGS/CBME/CBMENeuralControl.html Details about the University of Kentucky and the Center for Biomedical Engineering can be obtained on the web at http://www.uky.edu; http://www.uky.edu/RGS/CBME. The University of Kentucky is located in the rolling hills of the Bluegrass Country and has a diverse campus. The Center for Biomedical Engineering is a multidisciplinary center in the Graduate School. We have strong ties to the Medical Center and the School of Engineering. Ranu Jung, Ph.D. email:jung@pop.uky.edu Center for Biomedical Engineering phone:606-257-5931 Wenner-Gren Research Lab. fax: 606-257-1856 University of Kentucky http://www.uky.edu/RGS/CBME/jung.html Lexington, KY 40506-0070 From john@dcs.rhbnc.ac.uk Sat Oct 5 10:48:28 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 KAA07714 for ; Sat, 5 Oct 1996 10:48:21 -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 KAA26703 for ; Sat, 5 Oct 1996 10:48:18 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa03384; 5 Oct 96 1:14:58 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa03381; 5 Oct 96 0:54:46 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa01784; 5 Oct 96 0:54:30 EDT Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa24609; 4 Oct 96 5:04:09 EDT Received: from [134.219.44.52] by CS.CMU.EDU id aa02142; 4 Oct 96 5:03:34 EDT Received: from localhost (localhost [127.0.0.1]) by platon.cs.rhbnc.ac.uk (8.6.9/8.6.9) with SMTP id JAA32168 ; Fri, 4 Oct 1996 09:40:40 +0100 From: John Shawe-Taylor Message-Id: <199610040840.JAA32168@platon.cs.rhbnc.ac.uk> X-Authentication-Warning: platon.cs.rhbnc.ac.uk: Host localhost didn't use HELO protocol To: Connectionists@cs.cmu.edu Subject: Technical Report Series in Neural and Computational Learning Date: Fri, 04 Oct 96 09:40:39 +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. ---------------------------------------- NeuroCOLT Technical Report NC-TR-96-049: ---------------------------------------- Extended Grzegorczyk Hierarchy in the BSS Model of Computability by Jean-Sylvestre Gakwaya, Universit\'e de Mons-Hainaut, Belgium Abstract: In this paper, we give an extension of the Grzegorczyk Hierarchy to the BSS theory of computability which is a generalization of the classical theory. We adapt some classical results related to the Grzegorczyk hierarchy in the new setting. ---------------------------------------- NeuroCOLT Technical Report NC-TR-96-050: ---------------------------------------- Learning from Examples and Side Information by Joel Ratsaby, Technion, Israel Vitaly Maiorov, Technion, Israel Abstract: We set up a theoretical framework for learning from examples and side information which enables us to compute the tradeoff between the sample complexity and information complexity for learning a target function in a Sobolev functional class $\cal F$. We use the notion of the {\em $n^{th}$ minimal radius of information} of Traub et. al. \cite{traub} and combine it with VC-theory to define a new quantity $I_{n,d}({\cal F})$ which measures the minimal approximation error of a target $g\in {\cal F}$ by the family of function classes with pseudo-dimension $d$ under a given side information which consists of any $n$ measurements on the target function $g$ constrained to being linear operators. By obtaining almost tight upper and lower bounds on $I_{n,d}({\cal F})$ we find an information operator $\hat{N}_n$ which yields a worst-case error no larger than a logarithmic factor in $n$ and $d$ than the lower bound on $I_{n,d}({\cal F})$. Hence to within a logarithmic factor it is the most efficient way of providing side information about a target $g$ under the constraint that the information operator must be linear and that the approximating class has pseudo-dimension $d$. ---------------------------------------- NeuroCOLT Technical Report NC-TR-96-051: ---------------------------------------- Complexity and Dimension by Felipe Cucker, City University of Hong Kong Pascal Koiran, Ecole Normale Superieure, Lyon, France Martin Matamala, Universidad de Chile, Chile Abstract: In this note we define a notion of sparseness for subsets of $\Ri$ and we prove that there are no sparse $\NPadd$-hard sets. Here we deal with additive machines which branch on equality tests of the form $x=y$ and $\NPadd$ denotes the corresponding class of sets decidable in nondeterministic polynomial time. Note that this result implies the separation $\Padd\not=\NPadd$ already known. ---------------------------------------- NeuroCOLT Technical Report NC-TR-96-052: ---------------------------------------- Semi-Algebraic Complexity -- Additive Complexity of Diagonalization of QuadraticForms by Thomas Lickteig, Universit\"at Bonn, Germany Klaus Meer, RWTH Aachen, Germany Abstract (for references see full paper): We study matrix calculation such as diagonalization of quadratic forms under the aspect of additive complexity and relate these complexities to the complexity of matrix multiplication. While in \cite{BKL} for multiplicative complexity the customary ``thick path existence'' argument was sufficient, here for additive complexity we need the more delicate finess of the real spectrum (cf. \cite{BCR}, \cite{Be}, \cite{KS}) to obtain a complexity relativization. After its outstanding success in semi-algebraic geometry the power of the real spectrum method in complexity theory becomes more and more apparent. Our discussions substantiate once more the signification and future r\^ole of this concept in the mathematical evolution of the field of real algebraic algorithmic complexity. A further technical tool concerning additive complexity is the structural transport metamorphosis from \cite{Li1} which constitutes another use of exponentiation and logarithm as it appears in the work on additive complexity by \cite{Gr} and \cite{Ri} through the use of \cite{Kh}. We confine ourselves here to diagonalization of quadratic forms. In the forthcoming paper \cite{LM} further such relativizations of additive complexity will be given for a series of matrix computational tasks. ---------------------------------------- NeuroCOLT Technical Report NC-TR-96-053: ---------------------------------------- Structural Risk Minimization over Data-Dependent Hierarchies by John Shawe-Taylor, Royal Holloway, University of London, UK Peter Bartlett, Australian National University, Australia Robert Williamson, Australian National University, Australia Martin Anthony, London School of Economics, UK Abstract: The paper introduces some generalizations of Vapnik's method of structural risk minimisation (SRM). As well as making explicit some of the details on SRM, it provides a result that allows one to trade off errors on the training sample against improved generalization performance. It then considers the more general case when the hierarchy of classes is chosen in response to the data. A result is presented on the generalization performance of classifiers with a ``large margin''. This theoretically explains the impressive generalization performance of the maximal margin hyperplane algorithm of Vapnik and co-workers (which is the basis for their support vector machines). The paper concludes with a more general result in terms of ``luckiness'' functions, which provides a quite general way for exploiting serendipitous simplicity in observed data to obtain better prediction accuracy from small training sets. Four examples are given of such functions, including the VC dimension measured on the sample. ---------------------------------------- NeuroCOLT Technical Report NC-TR-96-054: ---------------------------------------- Confidence Estimates of Classification Accuracy on New Examples by John Shawe-Taylor, Royal Holloway, University of London, UK Abstract: Following recent results (NeuroCOLT Technical Report NC-TR-96-053) showing the importance of the fat shattering dimension in explaining the beneficial effect of a large margin on generalization performance, the current paper investigates how the margin on a test example can be used to give greater certainty of correct classification in the distribution independent model. The results show that even if the classifier does not classify all of the training examples correctly, the fact that a new example has a larger margin than that on the misclassified examples, can be used to give very good estimates for the generalization performance in terms of the fat shattering dimension measured at a scale proportional to the excess margin. The estimate relies on a sufficiently large number of the correctly classified training examples having a margin roughly equal to that used to estimate generalization, indicating that the corresponding output values need to be `well sampled'. -------------------------------------------------------------------- ***************** 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 cas-cns@cns.bu.edu Sat Oct 5 10:48:32 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 KAA07717 for ; Sat, 5 Oct 1996 10:48:27 -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 KAA26705 for ; Sat, 5 Oct 1996 10:48:21 -0500 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id ab03384; 5 Oct 96 1:16:08 EDT Received: from DST.BOLTZ.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id ab03381; 5 Oct 96 0:54:48 EDT Received: from DST.BOLTZ.CS.CMU.EDU by DST.BOLTZ.CS.CMU.EDU id aa01789; 5 Oct 96 0:54:34 EDT Received: from MAILBOX.SRV.CS.CMU.EDU by B.GP.CS.CMU.EDU id aa04737; 4 Oct 96 14:52:50 EDT Received: from MAILBOX.SRV.CS.CMU.EDU by MAILBOX.SRV.CS.CMU.EDU id aa03988; 4 Oct 96 14:51:55 EDT Received: from CNS.BU.EDU by MAILBOX.SRV.CS.CMU.EDU id aa03985; 4 Oct 96 14:51:37 EDT Received: from mac-duffee.bu.edu by cns.bu.edu (SMI-8.6/BU-11/2/94) id OAA15927; Fri, 4 Oct 1996 14:24:42 -0400 Message-Id: <199610041824.OAA15927@cns.bu.edu> Date: Fri, 04 Oct 1996 14:24:57 -0400 From: CAs/CNS Cc: cas-cns@cns.bu.edu Subject: International Conference on VISION, RECOGNITION, ACTION Organization: Boston University - Cognitive and Neural Systems Reply-To: cas-cns@cns.bu.edu Mime-Version: 1.0 Content-Type: text/plain; charset=ISO-8859-1 Content-transfer-encoding: 8bit X-Newsreader: Yet Another NewsWatcher 2.3.0 ***** CALL FOR PAPERS ***** International Conference on VISION, RECOGNITION, ACTION: NEURAL MODELS OF MIND AND MACHINE May 28-31, 1997 Sponsored by the Center for Adaptive Systems and the Department of Cognitive and Neural Systems Boston University with financial support from the Defense Advanced Research Projects Agency and the Office of Naval Research This conference will include a day of tutorials (May 28) followed by 3 days of 21 invited lectures and contributed lectures and posters by experts on the biology and technology of how the brain and other intelligent systems see, understand, and act upon a changing world. Meeting updates can be found at http://cns-web.bu.edu/cns-meeting/. Hotel and restaurant information can also be found here. CONFIRMED INVITED SPEAKERS AND PROGRAM OUTLINE WEDNESDAY, MAY 28, 1997 TUTORIALS STEPHEN GROSSBERG "Vision, Brain, and Technology" (3 hours in two 1-1/2 hour lectures) This tutorial will provide a self-contained introduction to recent models of how the brain sees. It will also illustrate how these models have been used to help solve difficult image processing problems in technology. The biological part will discuss neural models of visual form, color, depth, figure-ground separation, motion, and attention, and how these several processes cooperate to generate complex percepts. The tutorial will build a theoretical bridge between data about visual perception and data about the architecture and dynamics of the visual brain. Technological applications to image restoration, texture labeling, figure-ground separation, and related problems will be described. GAIL CARPENTER "Self-Organizing Neural Networks for Learning, Recognition, and Prediction: ART Architectures and Applications" (2 hours) In 1976, Stephen Grossberg introduced adaptive resonance as a theory of human cognitive information processing. Over the past decade, the theory has led to an evolving series of real-time neural networks (ART models) that self-organize recognition categories in response to arbitrary sequences of input patterns. The intrinsic stability of an ART system allows rapid learning of new information while essential components of previously learned patterns are preserved. This tutorial will describe basic ART design principles, analytic tools, and benchmark simulations. Both unsupervised networks such as ART 1, ART 2, ART 3, and fuzzy ART, and supervised learning architectures such as ARTMAP, fuzzy ARTMAP, and ART-EMAP will be discussed. Successful applications of the ART and ARTMAP networks, including the Boeing parts retrieval CAD system, automatic mapping from remote sensing satellite measurements, and medical database prediction will be outlined. Computational elements of the recently developed dART and dARTMAP networks, that feature distributed code representations, will also be introduced. ERIC SCHWARTZ "Algorithms and Hardware for the Application of Space-Variant Active Vision to High Performance Machine Vision" (2 hours) The term space-variance refers to the fact that all higher vertebrate visual systems are based on spatial architectures which have non-constant resolution across the visual field. It has been shown that such architectures can lead to up to four orders of magnitude of compression in the space-complexity of vision tasks. However, there are fundamental algorithmic and hardware problems involved in the exploitation of these observations in computer vision, many of which have benefited from considerable progress during the past several years. In this tutorial, a brief outline of the anatomical basis for the notion of space-variance will be provided. Several examples of space-variant active vision systems will be then be discussed, focusing on the hardware specifications for sensors, optics, actuators and DSP based parallel processors. Finally, a review of the algorithmic aspects of these systems will be presented, including issues related to early vision (i.e., edge enhancement via nonlinear diffusion methods), and to pattern matching, based on recent development of an exponential chirp algorithm which can perform high-speed quasi-shift invariant processing on logarithmic image architectures. Functioning examples of space-variant active vision systems based on these developments will be demonstrated, included a miniature visually guided autonomous vehicle, a machine vision system for reading license plates of high-speed vehicles for traffic control, and a blind-prosthetic device based on a "wearable" active vision system. ******************** TUTORIAL BIOSKETCHES: GAIL CARPENTER is professor in the departments of Cognitive and Neural Systems (CNS) and Mathematics at Boston University. She is the CNS Director of Graduate Studies; 1989 Vice-President and 1994-96 Secretary of the International Neural Network Society (INNS); organization chair of the 1988 INNS annual meeting; and a member of the editorial boards of Brain Research, IEEE Transactions on Neural Networks, Neural Computation, and Neural Networks. She has served on the INNS Board of Governors since its founding in 1987, and is a member of the Council of the American Mathematical Society. She is a leading architect of the Adaptive Resonance Theory (ART) family of architectures for fast learning, pattern recognition, and prediction of nonstationary databases, including both unsupervised (ART 1, ART 2, ART 2-A, ART 3, fuzzy ART, distributed ART) and supervised (ARTMAP, fuzzy ARTMAP, ART-EMAP, distributed ARTMAP) ART networks. These systems have been used for a wide range of applications, such as medical diagnosis, remote sensing, automatic target recognition, mobile robots, and database management. Her earlier research includes the development, computational analysis, and applications of neural models of nerve impulse generation (Hodgkin-Huxley equations), vision, cardiac rhythms, and circadian rhythms. Professor Carpenter received her graduate training in mathematics at the University of Wisconsin and was a faculty member at MIT and Northeastern University before moving to Boston University. STEPHEN GROSSBERG is Wang Professor of Cognitive and Neural Systems and Professor of Mathematics, Psychology, and Biomedical Engineering at Boston University. He is the founder and Director of the Center for Adaptive Systems, as well as the founder and Chairman the Department of Cognitive and Neural Systems. He founded and was first President of the International Neural Network Society and also founded and is co-editor-in-chief of the Society's journal, Neural Networks. Grossberg was General Chairman of the first IEEE International Conference on Neural Networks. He is on the editorial boards of Brain Research, Journal of Cognitive Neuroscience, Behavioral and Brain Sciences, Neural Computation, IEEE Transactions on Neural Networks, and Adaptive Behavior. He organized two multi-institutional Congressional Centers of Excellence for research on biological neural networks and their technological applications. He received the IEEE Neural Network Pioneer award, the INNS Leadership Award, the Thinking Technology Award of the Boston Computer Society, and is a Fellow of the American Psychological Association and the Society of Experimental Psychologists. Grossberg and his colleagues have pioneered and developed a number of the fundamental principles, mechanisms, and architectures that form the foundation for contemporary neural network research. This work focuses upon the design principles and mechanisms which enable the behavior of individuals to adapt successfully in real-time to unexpected environmental changes. Core models pioneered by this approach include competitive learning and self-organizing feature maps, adaptive resonance theory, masking fields, gated dipole opponent processes, associative outstars and instars, associative avalanches, nonlinear cooperative-competitive feedback networks, boundary contour and feature contour systems, and vector associative maps. Grossberg received his graduate training at Stanford University and Rockefeller University, and was a Professor at MIT before assuming his present position at Boston University. ERIC SCHWARTZ received the PhD degree in High Energy Physics from Columbia University in 1973, followed by post-doctoral studies with E. Roy John at New York Medical College in neurophysiology. He has served as Associate Professor of Psychiatry at New York University Medical Center and Associate Professor of Computer Science at the Courant Institute of Mathematical Sciences. In 1985, he organized the first Symposium on Computational Neuroscience, and in 1989 founded Vision Applications, Inc. which designs and builds prototype machine vision systems based on space-variant active vision systems. Currently, he is Professor of Cognitive and Neural Systems, Electrical Engineering and Computer Systems and Anatomy and Neurobiology at Boston University. His research experience includes experimental particle physics, physiology (single cell recording), anatomy (2DG, PETT, MRI), computer graphics and image processing, VLSI design, actuator design, and neural modeling. ************************* THURSDAY, MAY 29, 1997 INVITED LECTURES Robert Shapley, New York University: Brain Mechanisms for Visual Perception of Occlusion George Sperling, University of California, Irvine: An Integrated Theory for Attentional Processes in Vision, Recognition, and Memory Patrick Cavanagh, Harvard University: Direct Recognition Stephen Grossberg, Boston University: Perceptual Grouping and Attention during Cortical Form and Motion Processing Robert Desimone, National Institute of Mental Health: Neuronal Mechanisms of Visual Attention Ennio Mingolla, Boston University: Visual Search Patricia Goldman-Rakic, Yale University Medical School: The Machinery of Mind: Models from Neurobiology Larry Squire, San Diego VA Medical Center: Brain Systems for Recognition Memory There will also be a contributed poster session on this day. FRIDAY, MAY 30, 1997 INVITED LECTURES Eric Schwartz, Boston University: Multi-Scale Vortex Structure of the Brain: Anatomy as Architecture in Biological and Machine Vision Lance Optican, National Eye Institute: Neural Control of Rapid Eye Movements John Kalaska, University of Montreal: Reaching to Visual Targets: Cerebral Cortical Neuronal Mechanisms Rodney Brooks, Massachusetts Institute of Technology: Models of Vision-Based Human Interaction There will also be a contributed talk session and a reception, followed by the KEYNOTE LECTURE Stuart Anstis, University of California, San Diego: Moving in Unexpected Directions SATURDAY, MAY 31, 1997 INVITED LECTURES Azriel Rosenfeld, University of Maryland: Some Viewpoints on Vision Terrance Boult, Lehigh University: Polarization Vision Allen Waxman, MIT Lincoln Laboratory: Opponent Color Models of Visible/IR Fusion for Color Night Vision Gail Carpenter, Boston University: Distributed Learning, Recognition, and Prediction in ART and ARTMAP Networks Tomaso Poggio, Massachusetts Institute of Technology: Representing Images for Visual Learning Michael Jordan, Massachusetts Institute of Technology: Graphical Models, Neural Networks, and Variational Approximations Andreas Andreou, Johns Hopkins University: Mixed Analog/Digital Neuromorphic VLSI for Sensory Systems Takeo Kanade, Carnegie Mellon University: Computational VLSI Sensors: Integrating Sensing and Processing There will also be a contributed poster session on this day. CALL FOR ABSTRACTS: Contributed abstracts by active modelers of vision, recognition, or action in cognitive science, computational neuroscience, artificial neural networks, artificial intelligence, and neuromorphic engineering are welcome. They must be received, in English, by January 31, 1997. Notification of acceptance will be given by February 28, 1997. A meeting registration fee must accompany each Abstract. See Registration Information below for details. The fee will be returned if the Abstract is not accepted for presentation and publication in the meeting proceedings. Each Abstract should fit on one 8 x 11" white page with 1" margins on all sides, single-column format, single-spaced, Times Roman or similar font of 10 points or larger, printed on one side of the page only. Fax submissions will not be accepted. Abstract title, author name(s), affiliation(s), mailing, and email address(es) should begin each Abstract. An accompanying cover letter should include: Full title of Abstract, corresponding author and presenting author name, address, telephone, fax, and email address. Preference for oral or poster presentation should be noted. (Talks will be 15 minutes long. Posters will be up for a full day. Overhead, slide, and VCR facilities will be available for talks.) Abstracts which do not meet these requirements or which are submitted with insufficient funds will be returned. The original and 3 copies of each Abstract should be sent to: CNS Meeting, c/o Cynthia Bradford, Boston University, Department of Cognitive and Neural Systems, 677 Beacon Street, Boston, MA 02215. The program committee will determine whether papers will be accepted in an oral or poster presentation, or rejected. REGISTRATION INFORMATION: Since seating at the meeting is limited, early registration is recommended. To register, please fill out the registration form below. Student registrations must be accompanied by a letter of verification from a department chairperson or faculty/research advisor. If accompanied by an Abstract or if paying by check, mail to: CNS Meeting, c/o Cynthia Bradford, Boston University, Department of Cognitive and Neural Systems, 677 Beacon Street, Boston, MA 02215. If paying by credit card, mail to the above address, or fax to (617) 353-7755. STUDENT FELLOWSHIPS: A limited number of fellowships for PhD candidates and postdoctoral fellows are available to at least partially defray meeting travel and living costs. The deadline for applying for fellowship support is January 31, 1997. Applicants will be notifed by February 28, 1997. Each application should include the applicant's CV, including name; mailing address; email address; current student status; faculty or PhD research advisor's name, address, and email address; relevant courses and other educational data; and a list of research articles. A letter from the listed faculty or PhD advisor on offiicial institutional stationery should accompany the application and summarize how the candidate may benefit from the meeting. Students who also submit an Abstract need to include the registration fee with their Abstract. Reimbursement checks will be distributed after the meeting. Their size will be determined by student need and the availability of funds. -------------------------------------------------- REGISTRATION FORM (Please Type or Print) Vision, Recognition, Action: Neural Models of Mind and Machine Boston University Boston, Massachusetts Tutorials: May 28, 1997 Meeting: May 29-31, 1997 Mr/Ms/Dr/Prof: Name: Affiliation: Address: City, State, Postal Code: Phone and Fax: Email: The conference registration fee includes the meeting program, reception, six coffee breaks, and the meeting proceedings. Two coffee breaks and a book of tutorial viewgraph copies will be covered by the tutorial registration fee. CHECK ONE: [ ] $55 Conference plus Tutorial (Regular) [ ] $40 Conference plus Tutorial (Student) [ ] $35 Conference Only (Regular) [ ] $25 Conference Only (Student) [ ] $30 Tutorial Only (Regular) [ ] $25 Tutorial Only (Student) Method of Payment: [ ] Enclosed is a check made payable to "Boston University". Checks must be made payable in US dollars and issued by a US correspondent bank. Each registrant is responsible for any and all bank charges. [ ] I wish to pay my fees by credit card (MasterCard, Visa, or Discover Card only). Type of card: Name as it appears on the card: Account number: Expiration date: Signature and date: --------------------------------------------------