From harnad@cogsci.soton.ac.uk Sun Nov 17 04:59:23 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 EAA07750 for ; Sun, 17 Nov 1996 04:59:15 -0600 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 EAA04963 for ; Sun, 17 Nov 1996 04:59:13 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa01519; 16 Nov 96 16:14:35 EST Received: from OLS.IUS.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa01504; 16 Nov 96 15:55:36 EST Received: from OLS.IUS.CS.CMU.EDU by ols.ius.cs.cmu.edu id aa04438; 16 Nov 96 15:54 EST Received: from EDRC.CMU.EDU by B.GP.CS.CMU.EDU id ab28816; 16 Nov 96 15:28:14 EST Received: from [152.78.128.78] by EDRC.CMU.EDU id aa29507; 16 Nov 96 15:27:40 EST Received: from cogsci.soton.ac.uk (neuro.psy.soton.ac.uk [152.78.226.32]) by beech.soton.ac.uk (8.6.12/hub-8.5a) with SMTP id UAA23513; Sat, 16 Nov 1996 20:26:45 GMT Received: from cogsci.ecs.soton.ac.uk by cogsci.soton.ac.uk (5.x/SMI-SVR4) id AA21850; Sat, 16 Nov 1996 20:25:30 GMT From: Stevan Harnad Date: Sat, 16 Nov 96 20:25:18 GMT Message-Id: <6298.9611162025@cogsci.ecs.soton.ac.uk> To: cogneuro@ptolemy-ethernet.arc.nasa.gov, connectionists@cs.cmu.edu, neuro1-l%uicvm.BITNET@cunyvm.cuny.edu, neuron@cattell.psych.upenn.edu, PSYCOLOQUY Subject: Long-Term Potentiation: BBS Call for Commentators Below is the abstract of a forthcoming BBS target article on: LONG-TERM POTENTIATION: WHAT'S LEARNING GOT TO DO WITH IT? by Tracey J. Shors & Louis D. Matzel This article has been accepted for publication in Behavioral and Brain Sciences (BBS), an international, interdisciplinary journal providing Open Peer Commentary on important and controversial current research in the biobehavioral and cognitive sciences. Commentators must be BBS Associates or nominated by a BBS Associate. To be considered as a commentator for this article, to suggest other appropriate commentators, or for information about how to become a BBS Associate, please send EMAIL to: bbs@cogsci.soton.ac.uk or write to: Behavioral and Brain Sciences Department of Psychology University of Southampton Highfield, Southampton SO17 1BJ UNITED KINGDOM http://www.princeton.edu/~harnad/bbs/ http://www.cogsci.soton.ac.uk/bbs/ ftp://ftp.princeton.edu/pub/harnad/BBS/ ftp://ftp.cogsci.soton.ac.uk/pub/bbs/ gopher://gopher.princeton.edu:70/11/.libraries/.pujournals If you are not a BBS Associate, please send your CV and the name of a BBS Associate (there are currently over 10,000 worldwide) who is familiar with your work. All past BBS authors, referees and commentators are eligible to become BBS Associates. To help us put together a balanced list of commentators, please give some indication of the aspects of the topic on which you would bring your areas of expertise to bear if you were selected as a commentator. An electronic draft of the full text is available for inspection by anonymous ftp (or gopher or world-wide-web) according to the instructions that follow after the abstract. ____________________________________________________________________ LONG-TERM POTENTIATION: WHAT'S LEARNING GOT TO DO WITH IT? Tracey J. Shors & Louis D. Matzel Department of Psychology and Program in Neuroscience, Princeton University, Princeton, New Jersey 08544 shors@pucc.princeton.edu Department of Psychology, Program in Biopsychology and Behavioral Neuroscience, Rutgers University, New Brunswick, New Jersey 08903 matzel@rci.rutgers.edu KEYWORDS: NMDA, synaptic plasticity, Hebbian synapses, calcium, hippocampus, theta rhythm, spatial learning, classical conditioning, attention, arousal, memory systems ABSTRACT: Long-term potentiation (LTP) is operationally defined as a long-lasting increase in synaptic efficacy which follows high-frequency stimulation of afferent fibers. Since the first full description of the phenomenon in 1973, exploration of the mechanisms underlying LTP induction has been one of the most active areas of research in neuroscience. Of principal interest to those who study LTP, particularly LTP in the mammalian hippocampus, is its presumed role in the establishment of stable memories, a role consistent with "Hebbian" descriptions of memory formation. Other characteristics of LTP, including its rapid induction, persistence, and correlation with natural brain rhythms, provide circumstantial support for this connection to memory storage. Nonetheless, there is little empirical evidence that directly links LTP to the storage of memories. In this commentary, we review a range of cellular and behavioral characteristics of LTP, and evaluate whether those characteristics are consistent with the purported role of hippocampal LTP in memory formation. We suggest that much of the present focus on LTP reflects a preconception that LTP is a learning mechanism, although the empirical evidence often suggests that LTP is unsuitable for such a role. As an alternative to serving as a memory storage device, we propose that LTP may serve as a neural equivalent to an arousal or attention device in the brain. Accordingly, LTP is suggested to nonspecifically increase the effective salience of discrete external stimuli and thereby is capable of facilitating the induction of memories at distant synapses. In an environment open to critical inquiry, other hypotheses regarding the functional utility of this intensely studied mechanism are conceivable; the intent of this article is not exclusively to promote a single hypothesis, but rather to stimulate discussion about the neural mechanisms that are likely to underlie memory storage, and to appraise whether LTP can reasonably be considered a viable candidate for such a mechanism. -------------------------------------------------------------- To help you decide whether you would be an appropriate commentator for this article, an electronic draft is retrievable by anonymous ftp from ftp.princeton.edu according to the instructions below (the filename is bbs.shors). Please do not prepare a commentary on this draft. Just let us know, after having inspected it, what relevant expertise you feel you would bring to bear on what aspect of the article. ------------------------------------------------------------- These files are also on the World Wide Web and the easiest way to retrieve them is with Netscape, Mosaic, gopher, archie, veronica, etc. Here are some of the URLs you can use to get to the BBS Archive: http://www.princeton.edu/~harnad/bbs/ http://www.cogsci.soton.ac.uk/bbs/Archive/bbs.shors.html ftp://ftp.princeton.edu/pub/harnad/BBS/bbs.shors ftp://ftp.cogsci.soton.ac.uk/pub/bbs/Archive/bbs.shors gopher://gopher.princeton.edu:70/11/.libraries/.pujournals To retrieve a file by ftp from an Internet site, type either: ftp ftp.princeton.edu or ftp 128.112.128.1 When you are asked for your login, type: anonymous Enter password as queried (your password is your actual userid: yourlogin@yourhost.whatever.whatever - be sure to include the "@") cd /pub/harnad/BBS To show the available files, type: ls Next, retrieve the file you want with (for example): get bbs.shors When you have the file(s) you want, type: quit From harnad@cogsci.soton.ac.uk Sun Nov 17 04:59:25 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 EAA07753 for ; Sun, 17 Nov 1996 04:59:18 -0600 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 EAA04965 for ; Sun, 17 Nov 1996 04:59:16 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id ab01519; 16 Nov 96 16:17:02 EST Received: from OLS.IUS.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id ab01504; 16 Nov 96 15:55:38 EST Received: from OLS.IUS.CS.CMU.EDU by ols.ius.cs.cmu.edu id aa04442; 16 Nov 96 15:55 EST Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa28861; 16 Nov 96 15:31:17 EST Received: from beech.soton.ac.uk by CS.CMU.EDU id aa04685; 16 Nov 96 15:30:59 EST Received: from cogsci.soton.ac.uk (neuro.psy.soton.ac.uk [152.78.226.32]) by beech.soton.ac.uk (8.6.12/hub-8.5a) with SMTP id UAA23660; Sat, 16 Nov 1996 20:30:34 GMT Received: from cogsci.ecs.soton.ac.uk by cogsci.soton.ac.uk (5.x/SMI-SVR4) id AA21928; Sat, 16 Nov 1996 20:29:18 GMT From: Stevan Harnad Date: Sat, 16 Nov 96 20:29:06 GMT Message-Id: <6310.9611162029@cogsci.ecs.soton.ac.uk> To: cogneuro@ptolemy-ethernet.arc.nasa.gov, connectionists@cs.cmu.edu, Eye Movement List , neuro1-l%uicvm.BITNET@cunyvm.cuny.edu, neuron@cattell.psych.upenn.edu, PSYCOLOQUY Subject: Embodied Cognition: BBS Call for Commentators Cc: motor-mit@ai.mit.edu, neuromotor-control@ai.mit.edu Below is the abstract of a forthcoming BBS target article on: DEICTIC CODES FOR THE EMBODIMENT OF COGNITION by Dana H. Ballard, Mary M. Hayhoe, Polly K. Pook, & Rajesh P. N. Rao This article has been accepted for publication in Behavioral and Brain Sciences (BBS), an international, interdisciplinary journal providing Open Peer Commentary on important and controversial current research in the biobehavioral and cognitive sciences. Commentators must be BBS Associates or nominated by a BBS Associate. To be considered as a commentator for this article, to suggest other appropriate commentators, or for information about how to become a BBS Associate, please send EMAIL to: bbs@cogsci.soton.ac.uk or write to: Behavioral and Brain Sciences Department of Psychology University of Southampton Highfield, Southampton SO17 1BJ UNITED KINGDOM http://www.princeton.edu/~harnad/bbs/ http://www.cogsci.soton.ac.uk/bbs/ ftp://ftp.princeton.edu/pub/harnad/BBS/ ftp://ftp.cogsci.soton.ac.uk/pub/bbs/ gopher://gopher.princeton.edu:70/11/.libraries/.pujournals If you are not a BBS Associate, please send your CV and the name of a BBS Associate (there are currently over 10,000 worldwide) who is familiar with your work. All past BBS authors, referees and commentators are eligible to become BBS Associates. To help us put together a balanced list of commentators, please give some indication of the aspects of the topic on which you would bring your areas of expertise to bear if you were selected as a commentator. An electronic draft of the full text is available for inspection by anonymous ftp (or gopher or world-wide-web) according to the instructions that follow after the abstract. ____________________________________________________________________ DEICTIC CODES FOR THE EMBODIMENT OF COGNITION Dana H. Ballard, Mary M. Hayhoe, Polly K. Pook, and Rajesh P. N. Rao Computer Science Department University of Rochester Rochester, NY 14627, USA {dana, mary, pook, rao}@cs.rochester.edu KEYWORDS: deictic computations; embodiment; working memory; natural tasks; eye movements; brain computation; binding; sensory-motor tasks; pointers. ABSTRACT: To describe phenomena that occur at different time scales, computational models of the brain must necessarily incorporate different levels of abstraction. We argue that at time scales of approximately one-third of a second, orienting movements of the body play a crucial role in cognition and form a useful computational level. This level is more abstract than that used to capture neural phenomena yet is framed at a level of abstraction below that traditionally used to study high-level cognitive processes such as reasoning. We term this level the embodiment level. At the embodiment level, the constraints of the physical system determine the nature of cognitive operations. The key synergy is that, at time scales of about one-third second, the natural sequentiality of body movements can be matched to the natural computational economies of sequential decision systems. The way this is done is through a system of implicit reference termed deictic, whereby pointing movements are used to bind objects in the world to cognitive programs. The focus of this paper is to study how deictic bindings enable the solution of natural tasks. We show how deictic computation provides a mechanism for representing the essential features that link external sensory data with internal cognitive programs and motor actions. In particular, we argue that one of the central features of cognition, working memory, can be related to moment-by-moment dispositions of body features such as eye movements and hand movements. -------------------------------------------------------------- To help you decide whether you would be an appropriate commentator for this article, an electronic draft is retrievable by anonymous ftp from ftp.princeton.edu according to the instructions below (the filename is bbs.ballard). Please do not prepare a commentary on this draft. Just let us know, after having inspected it, what relevant expertise you feel you would bring to bear on what aspect of the article. ------------------------------------------------------------- These files are also on the World Wide Web and the easiest way to retrieve them is with Netscape, Mosaic, gopher, archie, veronica, etc. Here are some of the URLs you can use to get to the BBS Archive: http://www.princeton.edu/~harnad/bbs/ http://www.cogsci.soton.ac.uk/bbs/Archive/bbs.ballard.html ftp://ftp.princeton.edu/pub/harnad/BBS/bbs.ballard ftp://ftp.cogsci.soton.ac.uk/pub/bbs/Archive/bbs.ballard gopher://gopher.princeton.edu:70/11/.libraries/.pujournals To retrieve a file by ftp from an Internet site, type either: ftp ftp.princeton.edu or ftp 128.112.128.1 When you are asked for your login, type: anonymous Enter password as queried (your password is your actual userid: yourlogin@yourhost.whatever.whatever - be sure to include the "@") cd /pub/harnad/BBS To show the available files, type: ls Next, retrieve the file you want with (for example): get bbs.ballard When you have the file(s) you want, type: quit ---------- From ping@cogsci.richmond.edu Sun Nov 17 19:28:01 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 TAA17876 for ; Sun, 17 Nov 1996 19:27:56 -0600 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 TAA12043 for ; Sun, 17 Nov 1996 19:27:52 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa01500; 16 Nov 96 16:03:57 EST Received: from OLS.IUS.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa01498; 16 Nov 96 15:51:42 EST Received: from OLS.IUS.CS.CMU.EDU by ols.ius.cs.cmu.edu id aa04427; 16 Nov 96 15:51 EST Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa26995; 16 Nov 96 13:14:20 EST Received: from pinstripe.urich.edu by CS.CMU.EDU id aa03960; 16 Nov 96 13:14:15 EST Received: from mathcs.urich.edu (mathcs.urich.edu [141.166.104.153]) by pinstripe.urich.edu (8.8.2/8.7.3) with SMTP id NAA02393; Sat, 16 Nov 1996 13:30:23 -0500 (EST) Received: from cogsci.richmond.edu.urich.edu by mathcs.urich.edu (SMI-8.6/SMI-SVR4) id NAA17106; Sat, 16 Nov 1996 13:13:25 -0500 Received: by cogsci.richmond.edu.urich.edu (SMI-8.6/SMI-SVR4) id NAA14915; Sat, 16 Nov 1996 13:12:33 -0500 From: Ping Li Message-Id: <199611161812.NAA14915@cogsci.richmond.edu.urich.edu> Subject: Connection Science Vol. 8 (1) To: connectionists@cs.cmu.edu Date: Sat, 16 Nov 1996 13:12:33 -0500 (EST) Cc: brian+@andrew.cmu.edu X-Mailer: ELM [version 2.4 PL24] Content-Type: text CONNECTION SCIENCE Volume 8, No. 1, 1996 Cryptotype, overgeneralization and competition: A connectionist Model of the learning of English Reversive Prefixes Ping Li & Brian MacWhinney 3-30 A new theory of cerebellar function Franz Mechsner 31-54 A dynamic neural substrate and automatic perception switching Malcolm R.J. McQuoid & Chris H. Dobbyn 55-77 Csiszar's generalized error measures for gradient-descent-based optimizations in neural networks using the backpropagation algorithm P.S. Neelakanta, S. Abusalah, D. De Groff, R. Sudhaker & J.C. Park 79-114 Are rule-based neural networks biologically plausible? Armand de Callatay 115-151 HUMOR Degenerative grammar: The story of Outa Garrison W. Cottrell 153-154 Integrating neural and fuzzy reasoning James Hendler 155-157 From maruoka@maruoka.ecei.tohoku.ac.jp Mon Nov 18 16:33:53 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 QAA04887 for ; Mon, 18 Nov 1996 16:33:36 -0600 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 QAA28308 for ; Mon, 18 Nov 1996 16:33:35 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa04549; 18 Nov 96 10:21:29 EST Received: from OLS.IUS.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa04547; 18 Nov 96 10:02:16 EST Received: from OLS.IUS.CS.CMU.EDU by ols.ius.cs.cmu.edu id aa07281; 18 Nov 96 10:01 EST Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa20237; 17 Nov 96 22:30:43 EST Received: from [130.34.195.2] by CS.CMU.EDU id aa12978; 17 Nov 96 22:30:35 EST Received: from namihei.maruoka.ecei.tohoku.ac.jp (namihei.maruoka.ecei.tohoku.ac.jp [130.34.196.67]) by ecei.tohoku.ac.jp (8.7.5/3.4W) with SMTP id MAA29197 for ; Mon, 18 Nov 1996 12:30:15 +0900 (JST) Received: from taihei.maruoka.ecei.tohoku.ac.jp by namihei.maruoka.ecei.tohoku.ac.jp (4.1/6.4J.6) id AA27559; Mon, 18 Nov 96 12:30:16 JST Received: by taihei.maruoka.ecei.tohoku.ac.jp (4.1/6.4J.6) id AA08640; Mon, 18 Nov 96 12:25:19 JST Date: Mon, 18 Nov 96 12:25:19 JST From: Akira Maruoka Message-Id: <9611180325.AA08640@taihei.maruoka.ecei.tohoku.ac.jp> To: connectionists@cs.cmu.edu Cc: maruoka@ecei.tohoku.ac.jp Subject: ALT97 first ANNOUNCEMENT This CFP was sent to several mailing lists. Please accept my apologies if you receive multiple copies. Akira Maruoka ---------------------------------------------------------------------- CALL FOR PAPERS---ALT 97 The Eighth International Workshop on Algorithmic Learning Theory Sendai, Japan October 6-8, 1997 ______________________________________________________________________ The 8th International Workshop on Algorithmic Learning Theory (ALT'97) will be held in Sendai, Japan during October 6-8, 1997. The workshop is sponsored by the Japanese Society for Artificial Intelligence (JSAI) and Tohoku University. We invite submissions to ALT'97 in all areas related to algorithmic learning theory including (but not limited to): the design and analysis of learning algorithms, the theory of machine learning, computational logic of/for machine discovery, inductive inference, learning via queries, artificial and biological neural networks, pattern recognition, learning by analogy, Bayesian/MDL/MML estimation, statistical learning, inductive logic programming, application of learning to databases and biological sequence analysis. In addition to above theoretical topics, we invite submissions to two special tracks on data mining and case-based learning, aimed at promoting applications of theoretical ideas. INVITED TALKS. Invited talks will be given by Manuel Blum (UC Berkeley and City Univ. Hong Kong), Wolfgang Maass (Tech. Univ. Graz), Lenny Pitt (Univ. Illinois), and Masahiko Sato (Kyoto Univ.). SUBMISSIONS. Authors may either e-mail postscript files of their abstracts to mli@cs.cityu.edu.hk, or submit nine copies of their extended abstracts to: Professor Ming Li - ALT'97 Department of Computer Science City University of Hong Kong Tat Chee Avenue Kowloon, Hong Kong Abstracts must be received by April 1, 1997. Notification of acceptance or rejection will be (e)mailed to the first (or designated) author by May 19, 1997. Camera-ready copy of accepted papers will be due June 16, 1997. FORMAT. The submitted abstract should consist of a cover page with title, author names, postal and e-mail addresses, an approximately 200 word summary, and a body not longer than ten (10) pages of size A4 or 7x10.5 inches in twelve-point font. You may use appendices to include long but major proofs. If you submit hardcopies, double-sided printing is encouraged. POLICY. Each submitted abstract will be reviewed by the members of the program committee, and be judged on clarity, significance, and originality. Joint submissions to other conferences with published proceedings are not allowed. Papers that have appeared in journals or other conferences are not appropriate for ALT'97. Proceedings will be published as a volume in the Lecture Notes in Artificial Intelligence, Springer-Verlag, and will be available at the conference. Selected papers of ALT'97 will be invited to a special issue of the journal Theoretical Computer Science. One scholarship of $500US sponsored by IFIP TC 1.4 will be awarded to a student author (please mark student authors) in order to attend ALT'97. Conference chair: Professor Akira Maruoka Tohoku University Sendai, Japan 980 maruoka@ecei.tohoku.ac.jp Program committee chair: Ming Li (City Univ. HK and Univ. Waterloo) Program Committee: Naoki Abe (NEC, Japan) Nader Bshouty (Univ. Calgary, Canada) Nicolo Cesa-Bianchi (Milano Univ., Italy) Makoto Haraguchi (Hokkaido Univ., Japan) Hiroki Ishizaka (Kyushu Tech., Japan) Klaus P. Jantke (HTWK Leipzig, Germany) Philip Long (Nat. Univ. Singapore, Singapore) Shinichi Morishita (IBM Japan, Japan) Hiroshi Motoda (Osaka Univ., Japan) Yasubumi Sakakibara (Tokyo Denki Univ., Japan) Arun Sharma (New South Wales, Australia) Ayumi Shinohara (Kyushu Univ., Japan) Carl Smith (Univ. Maryland, USA) Frank Stephan (RKU, Germany) Naftali Tishby (Hebrew Univ., Israel) Paul Vitanyi (CWI, Netherlands) Les Valiant (Harvard, USA) Osamu Watanabe (Titech., Japan) Takashi Yokomori (UEC, Japan) Bin Yu (UC Berkeley, USA) Local arrangements chair: Professor Hirotomo Aso Graduate School of Engineering Tohoku University Sendai, Japan 980 alt97@maruoka.ecei.tohoku.ac.jp For more information, contact: Email: alt97@maruoka.ecei.tohoku.ac.jp Homepage: http://www.maruoka.ecei.tohoku.ac.jp/~alt97  From fayyad@MICROSOFT.com Mon Nov 18 16:33:55 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 QAA04890 for ; Mon, 18 Nov 1996 16:33:38 -0600 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 QAA28310 for ; Mon, 18 Nov 1996 16:33:36 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa04560; 18 Nov 96 10:31:10 EST Received: from OLS.IUS.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa04551; 18 Nov 96 10:03:05 EST Received: from OLS.IUS.CS.CMU.EDU by ols.ius.cs.cmu.edu id aa07290; 18 Nov 96 10:02 EST Received: from EDRC.CMU.EDU by B.GP.CS.CMU.EDU id ab20891; 17 Nov 96 23:47:59 EST Received: from mail5.microsoft.com by EDRC.CMU.EDU id aa04745; 17 Nov 96 23:47:32 EST Received: by INET-05-IMC.itg.microsoft.com with SMTP (Microsoft Exchange Server Internet Mail Connector Version 4.0.994.63) id <01BBD4C9.0C085BD0@INET-05-IMC.itg.microsoft.com>; Sun, 17 Nov 1996 20:51:03 -0800 Message-ID: From: Usama Fayyad To: "'connectionists@cs.cmu.edu'" Cc: "'GPS'" , "'Heikki Mannila'" , Data Mining and Knowledge Discovery Subject: Data Mining & knowledge Discovery Journal: contents vol 1:1 Date: Sun, 17 Nov 1996 20:47:27 -0800 X-Mailer: Microsoft Exchange Server Internet Mail Connector Version 4.0.994.63 Encoding: 95 TEXT ANNOUNCEMENT and CALL FOR PAPERS Below are the contents of the first issue of the new journal: Knowledge Discovery and Data Mining, Kluwer Academic Publishers. The journal is accepting submissions of works from a wide variety of fields that relate to data mining and knowledge discovery in databases (KDD). We accept regular research contributions, survey articles, application details papers, as well as short (2-page) application summaries. The goal is for Data Mining and Knowledge Discovery to become the premiere forum for publishing high quality original work from the wide variety of fields on which KDD draws, including: statistics, pattern recognition, database research and systems, modelling uncertainty and decision making, neural networks, machine learning, OLAP, data warehousing, high-performance and parallel computing, and visualization. The goal is to create a reference resource where researchers and practitioners in the area can lookup and communicate relevant work from a wide variety of fields. The journal's homepage provides detailed call for papers, description of the journal and its scope, and a list of the Editorial Board. Abstracts of the articles in the first issue and the editorial are also on-line. The home page is maintained at: http://www.research.microsoft.com/research/datamine - If you are interested in submitting a paper, please visit the homepage: http://www.research.microsoft.com/research/datamine to look up instructions. - if you would like a free sample issue sent to you, click on the link in http://www.research.microsoft.com/research/datamine and provide an address via the on-line form. Usama Fayyad, co-Editor-in-Chief Data Mining and Knowledge Discovery (datamine@microsoft.com) ======================================================================= Data Mining and Knowledge Discovery http://www.research.microsoft.com/research/datamine CONTENTS OF: Volume 1, Issue 1 ============================== For more details, abstracts, and on-line version of Editorial, see http://www.research.microsoft.com/research/datamine/vol1-1 ===========Volume 1, Number 1, March 1997=========== EDITORIAL by Usama Fayyad PAPERS ====== Statistical Themes and Lessons for Data Mining Clark Glymour, David Madigan, Daryl Pregibon, Padhraic Smyth Data Cube: A Relational Aggregation Operator Generalizing Group-by, Cross-Tab, and Sub Totals Jim Gray, Surajit Chaudhuri, Adam Bosworth, Andrew Layman, Don Reichart, Murali Venkatrao, Frank Pellow, IBM, Toronto, Hamid Pirahesh On Bias, Variance, 0/1 - loss, and the Curse-of-Dimensionality Jerome H. Friedman Bayesian Networks for Data Mining David Heckerman BRIEF APPLICATIONS SUMMARIES: ============================ Advanced Scout: Data Mining and Knowledge Discovery in NBA data Ed Colet, Inderpal Bhandari, Jennifer Parker, Zachary Pines, Rajiv Pratap, Krishnakumar Ramanujam ------------------------------------------------------------------------ To get a free sample copy of the above issue, visit the web page at http://www.research.microsoft.com/research/datamine Those who do not have web access may send their address to Kluwer by e-mail at: sdelman@wkap.com From lopez@physik.uni-wuerzburg.de Mon Nov 18 16:33:58 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 QAA04894 for ; Mon, 18 Nov 1996 16:33:42 -0600 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 QAA28312 for ; Mon, 18 Nov 1996 16:33:40 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id ab04560; 18 Nov 96 10:33:16 EST Received: from OLS.IUS.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id ab04551; 18 Nov 96 10:03:10 EST Received: from OLS.IUS.CS.CMU.EDU by ols.ius.cs.cmu.edu id aa07296; 18 Nov 96 10:03 EST Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa25970; 18 Nov 96 7:32:35 EST Received: from [132.187.40.1] by CS.CMU.EDU id aa15910; 18 Nov 96 7:31:06 EST Received: (from smap@localhost) by wptx01.physik.uni-wuerzburg.de (8.7.5/8.7.3/TPhys_S) id NAA24383 for ; Mon, 18 Nov 1996 13:30:40 +0100 (MEZ) From: Bernardo Lopez Received: from wptx14.physik.uni-wuerzburg.de(132.187.40.14) by wptx01.physik.uni-wuerzburg.de (smap V1.3) id sma024381 for ; Mon Nov 18 13:30:20 1996 Received: (from lopez@localhost) by wptx14.physik.uni-wuerzburg.de (8.7.5/8.7.3/TPhys_C) id NAA13542 for connectionists@cs.cmu.edu; Mon, 18 Nov 1996 13:30:19 +0100 (MEZ) Message-Id: <199611181230.NAA13542@wptx14.physik.uni-wuerzburg.de> Subject: Paper available: Learning by dilution in a Neural Network To: connectionists@cs.cmu.edu Date: Mon, 18 Nov 1996 13:30:18 +0100 (MEZ) X-Mailer: ELM [version 2.4 PL24 ME8b] MIME-Version: 1.0 Content-Type: text/plain; charset=US-ASCII Content-Transfer-Encoding: 7bit FTP-host: ftp.physik.uni-wuerzburg.de FTP-filename: /pub/preprint/1996/WUE-ITP-96-028.ps.gz The following manuscript is now available via anonymous ftp: (See below for the retrieval procedure) ------------------------------------------------------------------ "Learning by dilution in a Neural Network" B. Lopez and W. Kinzel Ref. WUE-ITP-96-028 Abstract A perceptron with N random weights can store of the order of N patterns by removing a fraction of the weights without changing their strengths. The critical storage capacity as a function of the concentration of the remaining bonds for random outputs and for outputs given by a teacher perceptron is calculated. A simple Hebb--like dilution algorithm is presented which in the teacher case reaches the optimal generalization ability. --------------------------------------------------------------------- Retrieval procedure: unix> ftp ftp.physik.uni-wuerzburg.de Name: anonymous Password: {your e-mail address} ftp> cd pub/preprint/1996 ftp> binary ftp> get WUE-ITP-96-028.ps.gz (*) ftp> quit unix> gunzip WUE-ITP-96-028.ps.gz e.g. unix> lp WUE-ITP-96-028.ps [15 pages] (*) can be replaced by "get WUE-ITP-96-028.ps". The file will then be uncompressed before transmission (slow!). _____________________________________________________________________ From gordon@aic.nrl.navy.mil Tue Nov 19 13:52:33 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 NAA20946 for ; Tue, 19 Nov 1996 13:52:14 -0600 Received: from cs.uwa.oz.au (bilby.cs.uwa.oz.au [130.95.1.11]) by lucy.cs.wisc.edu (8.7.6/8.7.3) with SMTP id NAA15031 for ; Tue, 19 Nov 1996 13:52:12 -0600 (CST) Received: from (warabi.cs.uwa.oz.au [130.95.1.13]) by cs.uwa.oz.au (8.6.8/8.5) with SMTP id BAA21589; Wed, 20 Nov 1996 01:28:27 +0800 Message-Id: <199611191728.BAA21589@cs.uwa.oz.au> From: gordon@aic.nrl.navy.mil To: reinforce@cs.uwa.edu.au Subject: workshop proposals Date: Tue, 19 Nov 96 10:55:48 EST REMINDER: The WORKSHOP PROPOSALS for ICML-97 are due by December 4, 1996, preferably by email to gordon@aic.nrl.navy.mil. For details about the conference and the Call for Workshop Proposals, see the ICML-97 Web site: http://cswww.vuse.vanderbilt.edu/~mlccolt/icml97/index.html Diana Gordon From mlittman@cs.duke.edu Tue Nov 19 13:53:39 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 NAA21017 for ; Tue, 19 Nov 1996 13:53:24 -0600 Received: from cs.uwa.oz.au (bilby.cs.uwa.oz.au [130.95.1.11]) by lucy.cs.wisc.edu (8.7.6/8.7.3) with SMTP id NAA15059 for ; Tue, 19 Nov 1996 13:53:21 -0600 (CST) Received: from (warabi.cs.uwa.oz.au [130.95.1.13]) by cs.uwa.oz.au (8.6.8/8.5) with SMTP id BAA21457; Wed, 20 Nov 1996 01:27:33 +0800 Message-Id: <199611191727.BAA21457@cs.uwa.oz.au> From: mlittman@cs.duke.edu (Michael L. Littman) To: connectionists@cs.cmu.edu, reinforce@cs.uwa.edu.au, reinforcement@cs.cmu.edu Subject: Paper available on convergence in reinforcement learning [connectionists] Date: Mon, 18 Nov 1996 15:10:54 -0500 (EST) Greetings, The following paper is now available by anonymous ftp (or the web). It is an extended version (with proofs and additional applications) of an earlier paper that appeared in ICML'96. -Michael -------------------------------------------------- URL: ftp://ftp.cs.brown.edu/pub/techreports/96/cs96-11.ps.Z Title: Generalized Markov Decision Processes: Dynamic-programming and Reinforcement-learning Algorithms Authors: Csaba Szepesva'ri and Michael L. Littman Tech report number: CS-96-11, Brown University Department of Computer Science Abstract: The problem of maximizing the expected total discounted reward in a completely observable Markovian environment, i.e., a Markov decision process (MDP), models a particular class of sequential decision problems. Algorithms have been developed for making optimal decisions in MDPs given either an MDP specification or the opportunity to interact with the MDP over time. Recently, other sequential decision-making problems have been studied prompting the development of new algorithms and analyses. We describe a new generalized model that subsumes MDPs as well as many of the recent variations. We prove some basic results concerning this model and develop generalizations of value iteration, policy iteration, model-based reinforcement-learning, and Q-learning that can be used to make optimal decisions in the generalized model under various assumptions. Applications of the theory to particular models are described, including risk-averse MDPs, exploration-sensitive MDPs, sarsa, Q-learning with spreading, two-player games, and approximate max picking via sampling. Central to the results are the contraction property of the value operator and a stochastic-approximation theorem that reduces asynchronous convergence to synchronous convergence. From kremer@running.dgcd.doc.ca Tue Nov 19 21:19:46 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 VAA28952 for ; Tue, 19 Nov 1996 21:19:36 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.7.6/8.7.3) with SMTP id VAA23117 for ; Tue, 19 Nov 1996 21:19:32 -0600 (CST) Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa04773; 18 Nov 96 14:53:27 EST Received: from FWA.IUS.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa04771; 18 Nov 96 14:36:12 EST Received: from FWA.IUS.CS.CMU.EDU by fwa.ius.cs.cmu.edu id aa11530; 18 Nov 96 14:35 EST Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa02958; 18 Nov 96 13:32:38 EST Received: from [142.92.37.179] by CS.CMU.EDU id aa19435; 18 Nov 96 13:30:20 EST Received: by running (4.1/SMI-4.1) id AA02138; Mon, 18 Nov 96 13:33:18 EST Date: Mon, 18 Nov 1996 13:33:17 -0500 (EST) From: "Stefan C. Kremer" Reply-To: stefan.kremer@crc.doc.ca To: Connectionists Mailing List Subject: NIPS 96 Workshop Announcement: Dynamical Recurrent Networks, Day 2 Message-Id: Mime-Version: 1.0 Content-Type: TEXT/PLAIN; charset=US-ASCII Content-Transfer-Encoding: QUOTED-PRINTABLE NIPS 96 Workshop Announcement: =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D= =3D=3D=3D=3D=3D Dynamical Recurrent Networks Post Conference Workshop Day 2 Organized by John Kolen and Stefan Kremer = =20 Saturday, December 7, 1996 Snowmass, Colorado Introduction: =20 There has been significant interest in recent years in dynamic recurrent neural networks and their application to control, system identification, signal processing, and time series analysis and prediction. Much of this work is simply an extension of techniques which work well for feedforward networks to recurrent networks. However, when dynamics are added to a system there are many complex issues which are not relevant to the study of feedforward nets, such as the existence of attractors and questions of stability, controllability, and observability.= =20 In addition, the architectures and learning algorithms that work well for feedforward systems are not necessarily useful or efficient in recurrent systems. =20 The first day of the workshop highlights the use of traditional results from systems theory and nonlinear dynamics to analyze the behavior of recurrent networks. The aim of the workshop is to expose recurrent network designers to the traditional frameworks available in these well established fields. A clearer understanding of the known results and open problems in these fields, as they relate to recurrent networks, will hopefully enable people working with recurrent networks to design more robust systems which can be more efficiently trained. This session will overview known results from systems theory and nonlinear dynamics which are relevant to recurrent networks, discuss their significance in the context of recurrent networks, and highlight open problems. (More information about Day 1 of the workshop can be found at: http://flute.lanl.gov/NIS-7_home_pages/jhowse/talk_abstracts.html). =20 The second day of the workshop addresses the issues of designing and selecting architectures and algorithms for dynamic recurrent networks. Unlike previous workshops, which have typically focussed on reporting the results of applying specific network architectures to specific problems, this session is intended to assist both users and developers of recurrent networks to select appropriate architectures and algorithms for specific tasks. In addition, this session will provide a backward flow of information -- a forum where researchers can listen to the needs of application developers. The wide variety, rapid development and diverse applications of recurrent networks are sure to make for exciting and controversial discussions.=20 Day 1, Friday, Dec. 6, 1996=20 =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D= =3D=3D More information about Day 1 of the workshop can be found at:=20 http://flute.lanl.gov/NIS-7_home_pages/jhowse/talk_abstracts.html Day 2, Saturday, Dec. 7, 1996 =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D= =3D=3D=3D=3D Target Audience:=20 This workshop is targeted at two groups. First, application developers faced with the task of selecting an appropriate tool for their problem will find this workshop invaluable. Second, researchers interested in studying and extending the capabilities of dynamic recurrent networks will = wish to communicate their findings and observations to other researchers in the area. In addition, these researchers will have an opportunity to listen to the needs of their technology's users.=20 Format: The format of the second day is designed to encouraged open discussion.=20 Presenters have provided 1 or 2 references to electronically accessible papers. At the workshop itself, the presenter will be asked to briefly (10 minutes) discuss highlights, conclusions, controversial issues or open problems of their research. This presentation will be followed by a 20 minute discussion period during which the expression of contrary opinions, related problems and speculation regarding solutions to open problems will be encouraged. The workshop will conclude with a one hour panel discussion.=20 Important Note to People Attending this Workshop:=20 The goal of this workshop is to offer an opportunity` for an open discussion of important issues in the area of dynamic networks. To achieve this goal, the presenters have been asked not to give a detailed description of their work but rather to give only a very brief synopsis in order to maximize the available discussion time. Attendees will get the most from this workshop if they are already familiar with the details of the work to be discussed. To make this possible, the presenters have made papers relevant to the discussions available electronically via the links on the workshop's web-page. Attendees who are not already familiar with the work of the presenters at the workshop are encouraged to examine the workshops web page (at: "http://running.dgcd.doc.ca/NIPS96/"), and=20 to retrieve and examine the papers prior to attending the workshop.=20 List of Talk Titles and Speakers: Learning Markovian Models for Sequence Processing=20 Yoshua Bengio, University of Montreal / AT&T Labs - Research Guessing Can Outperform Many Long Time Lag Algorithms J=FCrgen Schmidhuber, Istituto Dalle Molle di Studi sull'Intelligenza=20 =09=09Artificiale.=20 Sepp Hochreiter, Fakult=E4t f=FCr Informatik, Technische Universit=E4t M=FC= nchen.=20 Optimal Learning of Data Structure. Marco Gori, Universita' di Firenze How Embedded Memory in Recurrent Neural Network Architectures Helps Learning Long-term Temporal Dependencies.=20 T. Lin, B. Horne & C. Lee Giles, NEC Research Institute, Princeton, NJ.=20 Discovering the time scale of trends and periodic structure. Michael Mozer and Kelvin Fedrick, University of Colorado. Title to be announced.=20 Lee Feldkamp, Ford Motor Co. Labs.=20 Representation and learning issues for RNNs learning context free languages Janet Wiles and Brad Tonkes, Departments of Computer Science and Psychology= , University of Queensland Title to be announced.=20 Speaker to be Announced Long Short Term Memory.=20 Sepp Hochreiter, Fakult=E4t f=FCr Informatik, Technische Universit=E4t M=FC= nchen.=20 J=FCrgen Schmidhuber, Istituto Dalle Molle di Studi sull'Intelligenza=20 =09Artificiale.=20 Web page: Please note: more detailed and up to date information regarding this workshop, as well as the reference papers described above can be found at the Workshop's web page located at: =09http://running.dgcd.doc.ca/NIPS96/ -- Dr. Stefan C. Kremer, Research Scientist, Artificial Neural Systems 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=20 From devries@sarnoff.com Tue Nov 19 21:19:49 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 VAA28954 for ; Tue, 19 Nov 1996 21:19:37 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.7.6/8.7.3) with SMTP id VAA23119 for ; Tue, 19 Nov 1996 21:19:35 -0600 (CST) Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa05427; 19 Nov 96 1:52:42 EST Received: from VIE.IUS.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa05425; 19 Nov 96 1:38:02 EST Received: from VIE.IUS.CS.CMU.EDU by vie.ius.cs.cmu.edu id aa04716; 19 Nov 96 1:37 EST Received: from RI.CMU.EDU by B.GP.CS.CMU.EDU id aa06672; 18 Nov 96 16:03:19 EST Received: from peanut.sarnoff.com by RI.CMU.EDU id aa25470; 18 Nov 96 16:00:47 EST Received: from fire.sarnoff.com by peanut.sarnoff.com (4.1/SMI-4.1) id AA27194; Mon, 18 Nov 96 16:00:15 EST Date: Mon, 18 Nov 96 16:00:15 EST From: Aalbert De Vries x2456 Message-Id: <9611182100.AA27194@peanut.sarnoff.com> To: connectionists@cs.cmu.edu, ml@ics.uci.edu, vkm@eedsp.gatech.edu, idbw@eedsp.gatech.edu, ntcon@phoenix.ee.unsw.edu.au, gann@cs.iastate.edu, cells@tce.ing.uniroma1.it, neuron-request@CATTELL.psych.upenn.edu, wavelet@math.scarolina.edu Subject: NNSP*97 Workshop Announcement ************************************************************* * We apologize for multiple deliveries of this announcement * ************************************************************* 1997 IEEE Workshop on Neural Networks for Signal Processing 24-26 September 1997 Amelia Island Plantation, Florida FIRST ANNOUNCEMENT AND CALL FOR PAPERS Thanks to the sponsorship of the IEEE Signal Processing Society and the co-sponsorship of the IEEE Neural Network Council, we are proud to announce the seventh of a series of IEEE Workshops on Neural Networks for Signal Processing. Papers are solicited for, but not limited to, the following topics: * Paradigms: artificial neural networks, Markov models, fuzzy logic, inference net, evolutionary computation, nonlinear signal processing, and wavelets * Application areas: speech processing, image processing, OCR, robotics, adaptive filtering, communications, sensors, system identification, issues related to RWC, and other general signal processing and pattern recognition * Theories: generalization, design algorithms, optimization, parameter estimation, and network architectures * Implementations: parallel and distributed implementation, hardware design, and other general implementation technologies Instructions for submitting papers Prospective authors are invited to submit 5 copies of extended summaries of no more than 6 pages. The top of the first page of the summary should include a title, authors' names, affiliations, address, telephone and fax numbers and email address, if any. Camera-ready full papers of accepted proposals will be published in a hard-bound volume by IEEE and distributed at the workshop. Submissions should be sent to: Dr. Jose C. Principe IEEE NNSP'97 444 CSE Bldg #42 P.O. Box 116130 University of Florida Gainesville, FL 32611 Important Dates: **************************************************** * Submission of extended summary: January 27, 1997 * **************************************************** * Notification of acceptance: March 31, 1997 * Submission of photo-ready accepted paper: April 26, 1997 * Advanced registration: before July 1, 1997 Further Information Local Organizer Ms. Sharon Bosarge Telephone: 352-392-2585 Fax: 352-392-0044 e-mail: sharon@ee1.ee.ufl.edu World Wide Web http://www.cnel.ufl.edu/nnsp97/ Organization General Chairs Lee Giles (giles@research.nj.nec.com), NEC Research Nelson Morgan (morgan@icsi.berkeley.edu), UC Berkeley Proceeding Chair Elizabeth J. Wilson (bwilson@ed.ray.com), Raytheon Co. Publicity Chair Bert DeVries (bdevries@sarnoff.com), David Sarnoff Research Center Program Chair Jose Principe (principe@synapse.ee.ufl.edu), University of Florida Program Committee Les ATLAS Andrew BACK A. CONSTANTINIDES Federico GIROSI Lars Kai HANSEN Allen GORIN Yu-Hen HU Jenq-Neng HWANG Biing-Hwang JUANG Shigeru KATAGIRI Gary KUHN Sun-Yuan KUNG Richard LIPPMANN John MAKHOUL Elias MANOLAKOS Erkki OJA Tomaso POGGIO Tulay ADALI Volker TRESP John SORENSEN Takao WATANABE Raymond WATROUS Andreas WEIGEND Christian WELLEKENS About Amelia Island Plantation Amelia Island is in the extreme northeast Florida, across the St. Mary's river. The island is just 29 miles from Jacksonville International Airport, which is served by all major airlines. Amelia Island Plantation is a 1,250 acre resort/paradise that offers something for every traveler. The Plantation offers 33,000 square feet of workable meeting space and a staff dedicated to providing an efficient, yet relaxed atmosphere. The many amenities of the Plantation include 45 holes of championship golf, 23 Har-Tru tennis courts, modern fitness facilities, an award winning children's program, more than 7 miles of flora-filled bike and jogging trails, 21 swimming pools, diverse accommodations, exquisite dining opportunities, and of course, miles of glistening Atlantic beach front. From marwan@ee.usyd.edu.au Tue Nov 19 21:19:53 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 VAA28960 for ; Tue, 19 Nov 1996 21:19:42 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.7.6/8.7.3) with SMTP id VAA23123 for ; Tue, 19 Nov 1996 21:19:40 -0600 (CST) Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa05476; 19 Nov 96 2:07:35 EST Received: from VIE.IUS.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa05429; 19 Nov 96 1:39:01 EST Received: from VIE.IUS.CS.CMU.EDU by vie.ius.cs.cmu.edu id aa04733; 19 Nov 96 1:38 EST Received: from RI.CMU.EDU by B.GP.CS.CMU.EDU id aa14409; 18 Nov 96 23:28:19 EST Received: from sedal.sedal.su.OZ.AU by RI.CMU.EDU id aa27783; 18 Nov 96 23:27:35 EST Received: from morph (morph.sedal.usyd.EDU.AU [129.78.24.69]) by sedal.sedal.su.OZ.AU (8.6.9/8.6.9) with SMTP id PAA06885 for ; Tue, 19 Nov 1996 15:27:12 +1100 Date: Tue, 19 Nov 1996 15:23:59 +1100 (EST) From: Marwan Jabri X-Sender: marwan@morph To: Connectionists Subject: Research Positions (posted for a colleague) Message-ID: MIME-Version: 1.0 Content-Type: TEXT/PLAIN; charset=US-ASCII The research positions below are posted for a colleague Prof. Max Bennett (maxb@physiol.su.oz.au) ------------------------------------------------------------------------ Research positions for Electrical Engineers in Neurobiology. Two positions are sought for Honours Graduates in Electrical Engineering to participate in a research program funded by the National Health and Medical Research Council for a minimum of three years. This program involves theoretical analysis and modelling of how currents are generated at nerve terminals and subsequently flow in neurones and muscle cells to change their excitability. The program also involves experimental work in which the electrical properties of neurones and muscle cells are determined in order to provide quantitative evaluation of the parameters used in the electrical modelling. Incorporating some of this research for a PhD is also possible. Renumeration will be in the range of $25,000 to $30,000 per annum. For further information, contact Prof. Max Bennett, Neurobiology Laboratory, Dept. of Physiology, University of Sydney, NSW 2006 Australia or at maxb@physiol.su.oz.au From td@elec.uq.edu.au Tue Nov 19 21:19:57 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 VAA28957 for ; Tue, 19 Nov 1996 21:19:40 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.7.6/8.7.3) with SMTP id VAA23121 for ; Tue, 19 Nov 1996 21:19:37 -0600 (CST) Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id ab05427; 19 Nov 96 1:55:04 EST Received: from VIE.IUS.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id ab05425; 19 Nov 96 1:38:06 EST Received: from VIE.IUS.CS.CMU.EDU by vie.ius.cs.cmu.edu id aa04723; 19 Nov 96 1:37 EST Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa12958; 18 Nov 96 21:54:36 EST Received: from s4.elec.uq.edu.au by CS.CMU.EDU id aa24902; 18 Nov 96 21:52:44 EST Received: (from td@localhost) by s4.elec.uq.edu.au (8.7.5/8.6.12) id MAA21705; Tue, 19 Nov 1996 12:52:32 +1000 (EST) From: Tom Downs Message-Id: <199611190252.MAA21705@s4.elec.uq.edu.au> Subject: postdoc available To: Connectionists@cs.cmu.edu Date: Tue, 19 Nov 1996 12:52:32 +1000 (EST) Cc: Tom Downs Reply-To: td@elec.uq.edu.au X-Mailer: ELM [version 2.4 PL25] Content-Type: text POSTDOCTORAL RESEARCH FELLOWSHIP Neural Networks Lab, Department of Electrical and Computer Engineering, University of Queensland, Brisbane, Australia, 4072. TOPIC : Estimating generalization performance in feedforward neural networks This 3-year position arises following the award of an Australian Research Council grant for a project in the area of generalization performance estimation. The ideal candidate will have a strong background in applied probability and mathematical statistics and will be capable of building upon the recent contributions to the field made by engineers, computer scientists and physicists. Good programming skills (preferably in C or C++) and good interpersonal skills will also be expected. The position is available from early in 1997. Salary will be at the level of a University of Queensland postdoctoral position and will start at around A$38,000 per annum with annual increments. To apply for this position, please send your CV and the names of three referees either to Prof T Downs at the above address or, by email, to td@elec.uq.edu.au. -- regards Dept. of Electrical and Computer Engineering, Tom Downs University of Queensland, QLD, Australia, 4072 Phone: +61-7-365-3869 Fax: +61-7-365-4999 INTERNET: td@s1.elec.uq.edu.au From hu@eceserv0.ece.wisc.edu Wed Nov 20 23:32:31 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 XAA19935 for ; Wed, 20 Nov 1996 23:32:25 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.7.6/8.7.3) with SMTP id XAA13746 for ; Wed, 20 Nov 1996 23:32:23 -0600 (CST) Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa06723; 19 Nov 96 19:35:02 EST Received: from VIE.IUS.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa06721; 19 Nov 96 19:15:09 EST Received: from VIE.IUS.CS.CMU.EDU by vie.ius.cs.cmu.edu id aa10755; 19 Nov 96 19:14 EST Received: from EDRC.CMU.EDU by B.GP.CS.CMU.EDU id aa04606; 19 Nov 96 16:48:06 EST Received: from eceserv0.ece.wisc.edu by EDRC.CMU.EDU id aa10376; 19 Nov 96 16:47:35 EST Received: by eceserv0.ece.wisc.edu (WE5:5.65c/ES5) id AA08557; Tue, 19 Nov 1996 15:47:31 -0600 Date: Tue, 19 Nov 1996 15:47:31 -0600 From: Yu Hen Hu Message-Id: <199611192147.AA08557@eceserv0.ece.wisc.edu> To: connectionists@cs.cmu.edu Submitted by Yu Hen Hu (hu@engr.wisc.edu) Please forgive me if you receive multiple copies of this posting. ******************************************************************** * LAST CALL FOR PAPERS DEADLINE 12/1/96 * * * * A Special Issue of IEEE Transactions on Signal Processing: * * Applications of Neural Networks to Signal Processing * * * ******************************************************************** Expected Publication Date: November 1997 Issue *** Submission Deadline: December 1, 1996 *** Guest Editors: A. G. Constantinides, Simon Haykin, Yu Hen Hu, Jenq-Neng Hwang, Shigeru Katagiri, Sun-Yuan Kung, T. A. Poggio Significant progress has been made applying artificial neural network (ANN) techniques to signal processing. From a signal processing perspective, it is imperative to understand how the neural network based algorithms are related to more conventional approaches in terms of performance, cost, and practical implementation issues. Questions like these demand honest, pragmatic, innovative, and imaginative answers. This special issue offers a unique forum for researchers and practitioners in this field to present their view on these important questions. We seek highest quality manuscripts which focus on the signal processing aspects of a neural network based algorithm, applications or implementation. Topics of interests include, but are not limited to: Neural network based signal detection, classification, and understanding algorithms. Nonlinear system identification, signal prediction, modeling, adaptive filtering, and neural network learning algorithms. Neural network applications to biomedical signal processing, including medical imaging, Electrocardiogram, EEG, and related topics. Signal processing algorithms for biological neural system modeling Comparison of neural network based approach with conventional signal processing algorithms for solving real world signal processing tasks. Real world signal processing applications based on neural networks. Fast and parallel algorithms for efficient implementation of neural networks based signal processing systems. Prospective authors are encouraged to SUBMIT MANUSCRIPTS BY DECEMBER 1, 1996 to: Professor Yu-Hen Hu E-mail: hu@engr.wisc.edu Univ. of Wisconsin - Madison, Phone: (608) 262-6724 Dept. of Electrical and Computer Engineering Fax: (608) 262-1267 1415 Engineering Drive Madison, WI 53706-1691 U.S.A. On the cover letter, indicate the manuscript is submitted to the special issue on neural network for signal processing . All manuscripts should conform to the submission guideline detailed in the "information for authors" printed in each issue of the IEEE Transactions on Signal Processing. Specifically, the length of each manuscript should not exceed 30 double-spaced pages. SCHEDULE Manuscript received by: December 1, 1996 Completion of initial review: March 31, 1997 Final manuscript received by : June 30, 1997 Expected publication date: November, 1997 DISTINGUISHED GUEST EDITORS Prof. A. G. Constantinides, Imperial College, UK, a.constantinides@romeo.ic.ac.uk Prof. Simon Haykin, McMaster University, Canada, haykin@synapse.crl.mcmaster.ca Prof. Yu Hen Hu, Univ. of Wisconsin, U.S.A., hu@engr.wisc.edu Prof. Jenq-Neng Hwang, University of Washington, U.S.A., hwang@ee.washington.edu Dr. Shigeru Katagiri, ATR, JAPAN, katagiri@hip.atr.co.jp Prof. Sun-Yuan Kung, Princeton University, U.S.A., kung@princeton.edu Prof. T. A. Poggio, Massachusetts Inst. of Tech., U.S.A., tp-temp@ai.mit.edu From ping@cogsci.richmond.edu Wed Nov 20 23:32:38 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 XAA19944 for ; Wed, 20 Nov 1996 23:32:30 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.7.6/8.7.3) with SMTP id XAA13748 for ; Wed, 20 Nov 1996 23:32:26 -0600 (CST) Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa07865; 20 Nov 96 10:58:39 EST Received: from VIE.IUS.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa07863; 20 Nov 96 10:39:36 EST Received: from VIE.IUS.CS.CMU.EDU by vie.ius.cs.cmu.edu id aa15461; 20 Nov 96 10:39 EST Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa11850; 19 Nov 96 22:57:44 EST Received: from pinstripe.urich.edu by CS.CMU.EDU id aa00931; 19 Nov 96 22:56:59 EST Received: from mathcs.urich.edu (mathcs.urich.edu [141.166.104.153]) by pinstripe.urich.edu (8.8.2/8.7.3) with SMTP id XAA03104 for ; Tue, 19 Nov 1996 23:13:54 -0500 (EST) Received: from cogsci.richmond.edu.urich.edu by mathcs.urich.edu (SMI-8.6/SMI-SVR4) id WAA01952; Tue, 19 Nov 1996 22:56:12 -0500 Received: by cogsci.richmond.edu.urich.edu (SMI-8.6/SMI-SVR4) id WAA20946; Tue, 19 Nov 1996 22:55:18 -0500 From: Ping Li Message-Id: <199611200355.WAA20946@cogsci.richmond.edu.urich.edu> Subject: Re: Connection Science To: connectionists@cs.cmu.edu Date: Tue, 19 Nov 1996 22:55:17 -0500 (EST) X-Mailer: ELM [version 2.4 PL24] Content-Type: text A number of people asked me whether information about Connection Science is available on the web. Here is the information that I can find (from the publisher) which I'd like to share with you. "Connection Science is a broadly based scientific journal providing academic and professional researchers world-wide with a unique forum for the exchange of information on current neural computing or connectionist issues in human and artificial intelligence, cognitive science, computational neuroscience and advanced computer science. Connection Science is also available in electronic form over the Internet via CatchWord Ltd., a UK-based electronic publishing services company. For further information on how to subscribe and to view Connection Science via the CatchWord system please connect to http://www.catchword.co.uk/. Members of the CMU Connectionist News Group may subscribe to the printed copy at a special rate. Please contact the publisher for further details." (Tel: 1 800 354 1420 in USA or Canada; +44 (0) 1235 521154 world-wide). Journal Editor-in-Chief: Professor Noel E. Sharkey, Dept. of Computer Science, University of Sheffield, UK. *********************************************************************** Ping Li, Ph.D. Email: ping@cogsci.richmond.edu Department of Psychology http://www.urich.edu/~pli University of Richmond Phone: (804) 289-8125 Richmond, VA 23173, USA Fax: (804) 289-8943 *********************************************************************** From hu@eceserv0.ece.wisc.edu Thu Nov 21 02:48:07 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 CAA22102 for ; Thu, 21 Nov 1996 02:48:02 -0600 Received: from cs.uwa.oz.au (bilby.cs.uwa.oz.au [130.95.1.11]) by lucy.cs.wisc.edu (8.7.6/8.7.3) with SMTP id CAA15650 for ; Thu, 21 Nov 1996 02:47:59 -0600 (CST) Received: from (warabi.cs.uwa.oz.au [130.95.1.13]) by cs.uwa.oz.au (8.6.8/8.5) with SMTP id OAA06445; Thu, 21 Nov 1996 14:06:07 +0800 Message-Id: <199611210606.OAA06445@cs.uwa.oz.au> From: Yu Hen Hu To: Reinforce@cs.uwa.edu.au Date: Tue, 19 Nov 1996 15:47:14 -0600 Submitted by Yu Hen Hu (hu@engr.wisc.edu) Please forgive me if you receive multiple copies of this posting. ******************************************************************** * LAST CALL FOR PAPERS DEADLINE 12/1/96 * * * * A Special Issue of IEEE Transactions on Signal Processing: * * Applications of Neural Networks to Signal Processing * * * ******************************************************************** Expected Publication Date: November 1997 Issue *** Submission Deadline: December 1, 1996 *** Guest Editors: A. G. Constantinides, Simon Haykin, Yu Hen Hu, Jenq-Neng Hwang, Shigeru Katagiri, Sun-Yuan Kung, T. A. Poggio Significant progress has been made applying artificial neural network (ANN) techniques to signal processing. From a signal processing perspective, it is imperative to understand how the neural network based algorithms are related to more conventional approaches in terms of performance, cost, and practical implementation issues. Questions like these demand honest, pragmatic, innovative, and imaginative answers. This special issue offers a unique forum for researchers and practitioners in this field to present their view on these important questions. We seek highest quality manuscripts which focus on the signal processing aspects of a neural network based algorithm, applications or implementation. Topics of interests include, but are not limited to: .. Neural network based signal detection, classification, and understanding algorithms. .. Nonlinear system identification, signal prediction, modeling, adaptive filtering, and neural network learning algorithms. .. Neural network applications to biomedical signal processing, including medical imaging, Electrocardiogram, EEG, and related topics. .. Signal processing algorithms for biological neural system modeling .. Comparison of neural network based approach with conventional signal processing algorithms for solving real world signal processing tasks. .. Real world signal processing applications based on neural networks. .. Fast and parallel algorithms for efficient implementation of neural networks based signal processing systems. Prospective authors are encouraged to SUBMIT MANUSCRIPTS BY DECEMBER 1, 1996 to: Professor Yu-Hen Hu E-mail: hu@engr.wisc.edu Univ. of Wisconsin - Madison, Phone: (608) 262-6724 Dept. of Electrical and Computer Engineering Fax: (608) 262-1267 1415 Engineering Drive Madison, WI 53706-1691 U.S.A. On the cover letter, indicate the manuscript is submitted to the special issue on neural network for signal processing . All manuscripts should conform to the submission guideline detailed in the "information for authors" printed in each issue of the IEEE Transactions on Signal Processing. Specifically, the length of each manuscript should not exceed 30 double-spaced pages. SCHEDULE Manuscript received by: December 1, 1996 Completion of initial review: March 31, 1997 Final manuscript received by : June 30, 1997 Expected publication date: November, 1997 DISTINGUISHED GUEST EDITORS Prof. A. G. Constantinides, Imperial College, UK, a.constantinides@romeo.ic.ac.uk Prof. Simon Haykin, McMaster University, Canada, haykin@synapse.crl.mcmaster.ca Prof. Yu Hen Hu, Univ. of Wisconsin, U.S.A., hu@engr.wisc.edu Prof. Jenq-Neng Hwang, University of Washington, U.S.A., hwang@ee.washington.edu Dr. Shigeru Katagiri, ATR, JAPAN, katagiri@hip.atr.co.jp Prof. Sun-Yuan Kung, Princeton University, U.S.A., kung@princeton.edu Prof. T. A. Poggio, Massachusetts Inst. of Tech., U.S.A., tp-temp@ai.mit.edu From td@elec.uq.edu.au Thu Nov 21 17:47:36 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 RAA07823 for ; Thu, 21 Nov 1996 17:47:26 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.7.6/8.7.3) with SMTP id RAA29331 for ; Thu, 21 Nov 1996 17:47:23 -0600 (CST) Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa08765; 21 Nov 96 0:32:29 EST Received: from VIE.IUS.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa08763; 21 Nov 96 0:13:53 EST Received: from VIE.IUS.CS.CMU.EDU by vie.ius.cs.cmu.edu id aa20496; 21 Nov 96 0:13 EST Received: from EDRC.CMU.EDU by B.GP.CS.CMU.EDU id aa04657; 20 Nov 96 18:37:31 EST Received: from print.elec.uq.edu.au by EDRC.CMU.EDU id aa17942; 20 Nov 96 18:36:58 EST Received: (from td@localhost) by print.elec.uq.edu.au (8.6.12/8.6.12) id JAA29483 for connectionists@cs.cmu.edu; Thu, 21 Nov 1996 09:36:50 +1000 From: Tom Downs Message-Id: <199611202336.JAA29483@print.elec.uq.edu.au> Subject: PostDoc Available To: connectionists@cs.cmu.edu Date: Thu, 21 Nov 1996 09:36:48 +1000 (EST) X-Mailer: ELM [version 2.4ME+ PL12 (25)] MIME-Version: 1.0 Content-Type: text/plain; charset=US-ASCII Content-Transfer-Encoding: 7bit POSTDOCTORAL RESEARCH FELLOWSHIP Neural Networks Lab, Department of Electrical and Computer Engineering, University of Queensland, Brisbane, Australia, 4072. TOPIC : Estimating generalization performance in feedforward neural networks This 3-year position arises following the award of an Australian Research Council grant for a project in the area of generalization performance estimation. The ideal candidate will have a strong background in applied probability and mathematical statistics and will be capable of building upon the recent contributions to the field made by engineers, computer scientists and physicists. Good programming skills (preferably in C or C++) and good interpersonal skills will also be expected. The position is available from early in 1997. Salary will be at the level of a University of Queensland postdoctoral position and will start at around A$38,000 per annum with annual increments. To apply for this position, please send your CV and the names of three referees either to Prof T Downs at the above address or, by email, to td@elec.uq.edu.au. -- regards Dept. of Electrical and Computer Engineering, Tom Downs University of Queensland, QLD, Australia, 4072 Phone: +61-7-365-3869 Fax: +61-7-365-4999 INTERNET: td@elec.uq.edu.au From jhowse@squid.lanl.gov Fri Nov 22 09:16:08 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 JAA18394 for ; Fri, 22 Nov 1996 09:16:00 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.7.6/8.7.3) with SMTP id JAA01897 for ; Fri, 22 Nov 1996 09:15:56 -0600 (CST) Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa10068; 21 Nov 96 20:05:56 EST Received: from VIE.IUS.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa10046; 21 Nov 96 19:39:46 EST Received: from VIE.IUS.CS.CMU.EDU by vie.ius.cs.cmu.edu id aa27746; 21 Nov 96 19:38 EST Received: from EDRC.CMU.EDU by B.GP.CS.CMU.EDU id aa26856; 21 Nov 96 14:49:29 EST Received: from mailhost.lanl.gov by EDRC.CMU.EDU id aa23421; 21 Nov 96 14:48:53 EST Received: from squid.lanl.gov (squid.lanl.gov [128.165.56.33]) by mailhost.lanl.gov (8.7.6/8.7.3) with SMTP id MAA06155; Thu, 21 Nov 1996 12:48:39 -0700 (MST) Received: by squid.lanl.gov (4.1/SMI-4.1) id AA19897; Thu, 21 Nov 96 12:48:38 MST Date: Thu, 21 Nov 96 12:48:38 MST From: James Howse Message-Id: <9611211948.AA19897@squid.lanl.gov> To: connectionists@cs.cmu.edu Subject: NIPS*96 Workshop Announcement: Dynamical Recurrent Networks, Day 1 Cc: howse@lanl.gov, horne@castle.net Reply-To: howse@lanl.gov NIPS*96 Workshop Announcement Dynamical Recurrent Networks NIPS*96 Postconference Workshop Day 1 Organized by James Howse and Bill Horne Friday, December 6, 1996 Snowmass, Colorado Workshop Abstract There has been significant interest in recent years in dynamic recurrent neural networks and their application to control, system identification, signal processing, and time series analysis and prediction. Much of this work is simply an extension of techniques which work well for feedforward networks to recurrent networks. However, when dynamics are added to a system there are many complex issues which are not relevant to the study of feedforward nets, such as the existence of attractors and questions of stability, controllability, and observability. In addition, the architectures and learning algorithms that work well for feedforward systems are not necessarily useful or efficient in recurrent systems. The first day of the workshop highlights the use of traditional results from systems theory and nonlinear dynamics to analyze the behavior of recurrent networks. The aim of the workshop is to expose recurrent network designers to the traditional frameworks available in these well established fields. A clearer understanding of the known results and open problems in these fields, as they relate to recurrent networks, will hopefully enable people working with recurrent networks to design more robust systems which can be more efficiently trained. This session will overview known results from systems theory and nonlinear dynamics which are relevant to recurrent networks, discuss their significance in the context of recurrent networks, and highlight open problems. The second day of the workshop addresses the issues of designing and selecting architectures and algorithms for dynamic recurrent networks. Unlike previous workshops, which have typically focussed on reporting the results of applying specific network architectures to specific problems, this session is intended to assist both users and developers of recurrent networks to select appropriate architectures and algorithms for specific tasks. In addition, this session will provide a backward flow of information -- a forum where researchers can listen to the needs of application developers. The wide variety, rapid development and diverse applications of recurrent networks are sure to make for exciting and controversial discussions. ::::::::::::: Format for Day 1 The format for this session is a series of 30 minute talks with 5 minutes for specific questions, followed by time for open discussion after all of the talks. The talks will give a tutorial overview of traditional results from systems theory or nonlinear dynamics, discuss their relationship to some problem in recurrent neural networks, and then outline unresolved problems related to these results. The discussions will center around possible ways to resolve the open problems, as well as clarifying the understanding of established results. The goal of this session is to introduce more of the NIPS community to ideas from control theory and nonlinear dynamics, and to illustrate the utility of these ideas in analyzing and synthesizing recurrent networks. ::::::::::::: Web Sites for the Workshop Additional information concerning Day 1 can be found at http://flute.lanl.gov/NIS-7_home_pages/jhowse/talk_abstracts.html. Information about Day 2 can be obtained at http://running.dgcd.doc.ca/NIPS96/. ::::::::::::: Schedule for Friday, December 6th Morning Session (7:30-10:30am) Structural Neural Dynamics and Computation Xin Wang Dynamical Recognizers: What Languages Can Recurrent Neural Networks Recognize in Real Time? Cris Moore Decoding Discrete Structures from Fixed Points of Analog Hopfield Networks Arun Jagota Recurrent Networks and Supervised Learning Jennie Si Afternoon Session (4:00-7:00pm) System Theory of Recurrent Networks Eduardo D. Sontag Learning Controllers for Complex Behavioral Systems Shankar Sastry and Lara Crawford Neural Network Verification of Hybrid Dynamical System Stability Michael Lemmon ::::::::::::: Talk Abstracts Title: Structural Neural Dynamics and Computation Author: Xin Wang Xerox Corporation Abstract: Dynamics and computation of neural networks can be regarded as two types of meaning of mathematical equations that are used to describe dynamical and computational behaviors of the networks. They are in parallel to operational semantics and denotational semantics of computer programs written in programming languages. Lessons learned in study of formal semantics and impacts of structural programming and object-oriented programming methodologies tell us that a structural approach has to be taken, in order to deal with complexity in analysis and synthesis caused by large-sized neural networks. This talk will start with presenting some small-sized networks that possess very rich dynamical and bifurcational behaviors, ranging from convergent to chaotic and from saddle to period-doubling bifurcations, and then examine some conditions under which these types of behaviors are preserved by standard constructions such as Cartesian product and cascade. ---------- Title: Dynamical Recognizers: What Languages Can Recurrent Neural Networks Recognize in Real Time? Author: Cris Moore Computation, Dynamics, and Inference Santa Fe Institute Abstract: There has been considerable interest recently in using recurrent neural networks as dynamical models of language, complementary to the standard symbolic and grammatical approaches. Numerous researchers have shown that RNNs can recognize regular, context-free, and even context-sensitive languages in real time. We place these results in a mathematical framework by treating RNNs with varying activation functions as iterated maps with varying functional forms. We relate the classes of languages recognizable in real time by these different types of RNNs directly to "classical" language classes from computational complexity theory. We prove, for instance, that there are languages recognizable in real time with piecewise-linear or quadratic activations that linear functions cannot, and that there are languages recognizable with exponential or sinusoidal activations that are not recognizable by polynomial activations of any degree. Our methods are essentially identical to the Vapnik-Chervonenkis dimension. We also relate these results to Blum, Shub and Smale's definition of analog computation, as well as Siegelmann and Sontag's. ---------- Title: Decoding Discrete Structures from Fixed Points of Analog Hopfield Networks Author: Arun Jagota Department of Computer Science University of California, Santa Cruz Abstract: In this talk we examine the relationship between the fixed points of certain specialized families of binary Hopfield networks and certain stable regions of their associated analog Hopfield network families. More specifically, consider some specialized family F of binary Hopfield networks whose fixed points have some well-characterized structure. We consider an analog version of the family F obtained by replacing the hard-threshold neurons by sigmoidal ones and replacing the discrete dynamics of the binary model by a continuous one. We ask the question: can discrete structures identical to or similar to those that are fixed points in the binary family F be recovered from certain stable regions of the associated analog family? We obtain revealing answers for certain families. Our results lead to a better understanding of the recoverability of discrete structures from stable regions of analog networks. They have applications to solving discrete problems via analog networks. We also discuss many open mathematical problems that our studies reveal. Several of the results were obtained in joint work with Fernanda Botelho and Max Garzon. ---------- Title: Recurrent Networks and Supervised Learning Author: Jennie Si Department of Electrical Engineering Arizona State University Abstract: After several years of adventure, researchers in the field of artificial neural networks have reached a common consensus about what neural networks can do and what their limitations are. In particular, there has been some fundamental results on the existence of artificial neural networks for function approximation and nonlinear dynamic system modeling; on neural networks for associative memory applications, etc. Some theoretical advances were made in neural networks for control applications, in an adaptive setting. In this talk, the emphasis is given to some recent progress aiming at a quantitative evaluation of neural network performance for some fundamental tasks, e.g., static and dynamic approximation; computation issues in training neural networks characterized by both memory and computation complexities. All the above discussions will be based on neural network models representing nonlinear static and dynamic input-output systems as well as state space nonlinear dynamic systems. Further applications of the fundamental neural network theory to simulation based approximation technique for nonlinear dyanmic progarmming will also be discussed. This technique may represent an important and practically applicable dynamic programming solution to complex problems that invoke the dual course of large dimension and lack of an accurate mathematical model. ---------- Title: System Theory of Recurrent Networks Author: Eduardo D. Sontag Department of Mathematics Rutgers University Abstract: We consider general recurrent networks. These are described by the differential equations x' = S(Ax+Bu) , y = Cx , in continuous time, or the analogous discrete-time version. Here S(.) is a diagonal mapping of the form S(a,b,c,...) = (s(a),s(b),s(c),...) where s(.) is a scalar real map called the "activation" of the network. The vector x represents the state of the system, u is the time-dependent input signal, and y represents the measurements or outputs of the system. Recurrent networks whose activation s(.) is the identity function s(x)=x are precisely the linear systems studied in control theory. It is perhaps an amazing fact that a nontrivial and interesting system theory can be developed for recurrent nets whose activation is the one typically used in neural net practice, s(x)=tanh(x). (One reason that makes this fact surprising is that recurrent nets with this activation are, in a suitable sense, universal approximators for arbitrary nonlinear systems.) This talk will survey recent results by the speaker and several coauthors (Albertini, Dasgupta, Koiran, Koplon, Siegelmann, Sussmann) regarding issues of parameter identifiability, controllability, observability, system approximation, computability, parameter reconstruction, and sample complexity for learning and generalization. We provide simple algebraic tests for many properties, expressed in terms of the "weight" or parameter matrices (A,B,C) that characterize the system. ---------- Title: Learning Controllers for Complex Behavioral Systems Authors: Shankar Sastry and Lara Crawford Electronics Research Laboratory University of California, Berkeley Abstract: Biological control systems routinely guide complex dynamical systems, such as the human body, through complicated tasks, such as running or diving. Conventional control techniques, however, stumble with these problems, which have complex dynamics, many degrees of freedom, and an only partially specified desired task (e.g., "move forward fast," or "execute a one-and-one-half-somersault dive"). To address behaviorally-specified problems like these, we are using a biologically-inspired, hierarchical control structure, in which network-based controllers learn the controls required at each level of the hierarchy, and no system model is required. The encoding and decoding of the information passed between hierarchical levels, including both controller commands and behavioral feedback, is an important design issue affecting both the size of the controller network needed and the ease with which it can learn; we have used biological encoding schemes for inspiration wherever possible. For example, the lowest-level controller outputs an encoded torque profile; the encoding is based on the way biological pattern generators for single-joint movements restrict the allowed control torque profiles to a particular parametrized control family. Such an encoding removes all time dependence from the controller's consideration, simplifying the learning task considerably to one of function approximation. The implementation of the controller networks themselves could take several forms, but we have chosen to use radial basis functions, which have some advantages over conventional networks. Through a learning architecture with good encodings for both the controls and the desired behaviors, many of the difficulties in controlling complex behavioral systems can be overcome. In this talk, we apply the control structure described above, with 800-element networks and a form of supervised learning, to the problem of controlling a human diver. The system learns open-loop controls to steer a 16-DOF human model through various dives, including a one-and-one-half somersault pike and a one-and-one-half somersault with a full twist. ---------- Title: Neural Network Verification of Hybrid Dynamical System Stability Author: Michael Lemmon Department of Electrical Engineering University of Notre Dame Abstract: Hybrid dynamical systems (HDS) can occur when a smooth dynamical system is supervised by discrete-event dynamical system. Such systems are frequently found in computer-controlled systems. A key issue in the development of hybrid system controllers concerns verifying that the system possesses certain generic properties such as safety, stability, and optimality. It has been possible to study the verifiability of restricted classes of hybrid systems. Examples of such systems include switched systems consisting of first-order integrators [Alur et al.], hybrid systems whose "switching" surfaces satisfy certain invariance properties [Lemmon et al.], and planar hybrid systems [Guckenheimer]. The extension of these verification methods to more general systems [Deshpande et al.], however, appears to be computationally intractable. This is due in large part to the complex behaviours that such systems can demonstrate. Simulation experiments with a simple system consisting of switched integrators (relative degree greater than 2) suggest that the $\omega$-limit sets of these systems can be single fixed points, periodic points, or Cantor sets. Neural networks may provide one method for assisting in the analysis of hybrid systems. A neural network can be used to approximate the Poincare map of a switched hybrid system. Such methods can be extremely useful in verifying whether a given HDS exhibits asymptotically stable periodic behaviours. The purpose of this talk are twofold. First, a summary of the principal results and open research areas in hybrid systems will be given. Second, the talk will discuss recent results on the use of neural networks in the verification of hybrid system stability. From raffaele@caio.irmkant.rm.cnr.it Fri Nov 22 09:16:25 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 JAA18392 for ; Fri, 22 Nov 1996 09:15:55 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.7.6/8.7.3) with SMTP id JAA01894 for ; Fri, 22 Nov 1996 09:15:52 -0600 (CST) Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa10044; 21 Nov 96 19:55:18 EST Received: from VIE.IUS.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa10042; 21 Nov 96 19:38:57 EST Received: from VIE.IUS.CS.CMU.EDU by vie.ius.cs.cmu.edu id aa27739; 21 Nov 96 19:38 EST Received: from CS.CMU.EDU by B.GP.CS.CMU.EDU id aa25479; 21 Nov 96 13:55:05 EST Received: from [150.146.7.11] by CS.CMU.EDU id aa17078; 21 Nov 96 13:53:38 EST Received: by caio.irmkant.rm.cnr.it (AIX 3.2/UCB 5.64/4.03) id AA14245; Thu, 21 Nov 1996 20:00:15 -0600 Date: Thu, 21 Nov 1996 20:00:14 -0600 (CST) From: Raffaele Calabretta To: connectionists@cs.cmu.edu Cc: raffaele@caio.irmkant.rm.cnr.it Subject: paper available on diploid neural networks Message-Id: Mime-Version: 1.0 Content-Type: TEXT/PLAIN; charset=US-ASCII The following paper (to appear in Neural Processing Letters) is now available via anonymous ftp: ------------------------------------------------------------------------- "Two is better than one: a diploid genotype for neural networks" --------------------------------------------------------------- Raffaele Calabretta (1,3), Riccardo Galbiati (2), Stefano Nolfi (1) and Domenico Parisi (1) 1 Department of Neural Systems and Artificial Life Institute of Psychology, National Research Council e-mail: raffaele@caio.irmkant.rm.cnr.it 2 Department of Biology, University "Tor Vergata" 3 Centro di Studio per la Chimica del Farmaco, National Research Council Department of Pharmaceutical Studies, University "La Sapienza" Rome, Italy --------------------------------------------------------------------------- Abstract: In nature the genotype of many organisms exhibits diploidy, i.e., it includes two copies of every gene. In this paper we describe the results of simulations comparing the behavior of haploid and diploid populations of ecological neural networks living in both fixed and changing environments. We show that diploid genotypes create more variability in fitness in the population than haploid genotypes and buffer better environmental change; as a consequence, if one wants to obtain good results for both average and peak fitness in a single population one should choose a diploid population with an appropriate mutation rate. Some results of our simulations parallel biological findings. Key words: adaptation, diploidy, genetic algorithms, genotype-phenotype mapping, neural networks. _________________________________________________________________ FTP-host: gracco.irmkant.rm.cnr.it FTP-filename: /pub/raffaele/calabretta.diploidy.ps.Z The paper has been placed in the anonymous-ftp archive (see above for ftp-host) and is now available as a compressed postscript file named: calabretta.diploidy.ps.Z Retrieval procedure: unix> ftp gracco.irmkant.rm.cnr.it Name: anonymous Password: {your e-mail address} ftp> cd pub/raffaele ftp> bin ftp> get calabretta.diploidy.ps.Z ftp> quit unix> uncompress calabretta.diploidy.ps.Z e.g. unix> lpr calabretta.diploidy.ps (8 pages of output) The paper is also available on World Wide Web: http://kant.irmkant.rm.cnr.it/gral.html Comments welcome Raffaele Calabretta e-mail address: raffaele@caio.irmkant.rm.cnr.it From thimm@idiap.ch Sat Nov 23 00:33:00 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 AAA01294 for ; Sat, 23 Nov 1996 00:32:53 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.7.6/8.7.3) with SMTP id AAA14233 for ; Sat, 23 Nov 1996 00:32:51 -0600 (CST) Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa11700; 22 Nov 96 17:01:20 EST Received: from VIE.IUS.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa11696; 22 Nov 96 16:42:07 EST Received: from VIE.IUS.CS.CMU.EDU by vie.ius.cs.cmu.edu id aa04670; 22 Nov 96 16:41 EST Received: from EDRC.CMU.EDU by B.GP.CS.CMU.EDU id aa12520; 22 Nov 96 7:56:15 EST Received: from avoi.idiap.ch by EDRC.CMU.EDU id aa27922; 22 Nov 96 7:55:23 EST Received: from localhost.idiap.ch (localhost.idiap.ch [127.0.0.1]) by avoi.idiap.ch (8.7.3/8.7.3) with SMTP id NAA11805; Fri, 22 Nov 1996 13:54:46 +0100 (MET) Message-Id: <199611221254.NAA11805@avoi.idiap.ch> X-Authentication-Warning: avoi.idiap.ch: Host localhost.idiap.ch [127.0.0.1] didn't use HELO protocol To: Connectionists@cs.cmu.edu cc: thimm@idiap.ch Subject: CFP: Session at KES'97: Knowledge Extraction from and with Neural Networks Date: Fri, 22 Nov 1996 13:54:44 +0100 From: Georg Thimm Call for Papers Knowledge Extraction from and with Neural Networks A session organized by G. Thimm at the First International Conference on Conventional and Knowledge-Based Intelligent Electronic Systems, KES '97 21st - 23rd May 1997, Adelaide, Australia Electronics Association of South Australia (please see below for the KES call of papers) Successfully trained Neural networks contain a certain knowledge: applied to formerly unseen data, they give (often) a correct answer. However, this knowledge is usually difficult to access, although an intelligible qualitative or quantitative representation is of interest in research and development: - The performance on untrained data can be evaluated (in complement to statistical methods). - The extracted knowledge can be used in the development of more efficient algorithms. - The knowledge is of scientific interest. Suggested topics for papers are: - Knowledge extraction techniques from neural networks. - Neural network architectures designed for knowledge extraction. - Applications in which extracted knowledge plays a role. - Ways to represent knowledge extracted from neural networks. - Performance estimation of neural networks using extracted knowledge. - Methods that use knowledge extracted from a neural network (but not the network). Authors are invited (but not required) to point out how the extracted knowledge is used and why neural networks as a intermediate representation of knowledge are of advantage. SUBMISSION OF PAPERS * Papers must be written in English (5 to 10 pages maximum). * Paper presentation is about 20 minutes each including questions and discussions. * Include corresponding author with full name, address, telephone and fax numbers, E-Mail address. * Include presenter address and his/her 4 line resume for introduction purposes only. * Fax or E-Mail copies are not acceptable. * Please submit one original and three copies of camera ready paper (A4 size), two column format in Times or similar font style, 10 points with one inch margin on all four sides for review to: Georg Thimm IDIAP Rue de Simplon 4 C.P. 592 CH-1920 Switzerland Email: thimm@idiap.ch Tel: ++41 27 721 77 39 Fax: ++41 27 721 77 12 DEADLINES Receipt of papers for this session January 15, 1997 Notification of acceptance February 15, 1997 FURTHER INFORMATION Please look at http://www.idiap.ch/~thimm/KES_ses.html or contact G. Thimm for information on this special session or http://www.kes97.conf.au for the main conference. ================================================================== FIRST INTERNATIONAL CONFERENCE ON CONVENTIONAL AND KNOWLEDGE-BASED INTELLIGENT ELECTRONIC SYSTEMS, KES '97 21st - 23rd May 1997, Adelaide, Australia Electronics Association of South Australia CALL FOR PARTICIPATION The aim of this conference is to provide international forum for presentation of recent results in the general areas of Electronic Systems Design and Industrial Applications and Information Technology. Honorary Chair I. Sethi, WSA, USA Conference Chair L.C. Jain, UniSA, Australia General Chair C. Pay, EASA, Australia Conference Advisor R.P. Johnson, DSTO, Australia Conference Director N.M. Martin, DSTO, Australia Publicity Chair R.K. Jain, UA, Australia Publications Chair G.N. Allen, KES, Australia Austria Liaison Chairs F. Leisch, TUW K. Hornik, TUW Canada Liaison Chair C.W. de Silva, UBC New Zealand Liaison Chair N. Kasabov, UO Korea Liaison Chair J.H. Kim, KAIST Japan Liaison Chairs K. Hirota, TIT T. Tanaka, FIT Y. Sato, HU England Liaison Chair M.J. Taylor, UL France Liaison Chair E. Sanchez, Neurinfo USA Liaison Chairs N. Nayak, IBM Watson C.L. Karr, UA Polland Liaison Chair J. Kacprzyk, PAS Romania Liaison Chair M. Negoita, GEF Russia Liaison Chair V.I. Neprintsev, VSU Singapore Liaison Chair D. Mital, NTU The Netherlands Liaison Chair W. van Luenen, URL India Liaison Chairs B.S. Sonde, IISc A.N. Bannore, RLT Germany Liaison Chair U. Seiffert, UM Hungary Liaison Chair L.T. Koczy, TUB Italy Liaison Chair G. Guida, UB The conference will consist of plenary sessions, contributory sessions, poster papers, workshops and exhibition mainly on the theory and applications of conventional and knowledge-based intelligent systems using: . ARTIFICIAL NEURAL NETS . FUZZY SYSTEMS . EVOLUTIONARY COMPUTING . CHAOS THEORY THE TOPICS OF INTEREST The topics of interest include, but not limited to: Biomedical engineering; Consumer electronics; Electronic communication systems; Electronic control systems; Electronic production systems; Electronic security; Education and training; Industrial electronics; Knowledge- based intelligent engineering systems using expert systems, neural networks, fuzzy logic, evolutionary programming and chaos theory; Marketing; Mechatronics; Multimedia; Microelectronics; Optical electronics; Sensor technology; Signal processing; Virtual reality. SUBMISSION OF PAPERS * Papers must be written in English (5 to 10 pages maximum). * Paper presentation is about 20 minutes each including questions and discussions. * Include corresponding author with full name, address, telephone and fax numbers, E-Mail address. * Include presenter address and his/her 4 line resume for introduction purposes only. * Fax or E-Mail copies are not acceptable. * Please submit one original and three copies of the camera ready paper (A4 size), two column format in Times or similar font style, 10 points with one inch margin on all four sides for review to: Dr. L.C. Jain, Knowledge-based Intelligent Engineering Systems, School of Electronic Engineering, University of South Australia, Adelaide, The Levels, S.A., 5095, Australia. Tel: 61 8 302 3315 Fax: 61 8 302 3384 E-Mail etLCJ@Levels.UniSA.Edu.Au INVITED LECTURES The conference committee is also soliciting proposals for invited sessions focussing on new or emerging electronic technologies. Researchers, application engineers and managers are invited to submit proposals to Dr L.C. Jain by 31st October 1996. KEY DATES Conference and Exhibition - 22nd and 23rd May 1997 Workshops - 21st May 1997 Conference Dinner and Industry Awards for Excellence 22nd May 1997 DEADLINES Receipt of paper 31st December 1996 Receipts of workshop proposals - 31st October 1996 Notification of acceptance - 30th January 1997 REGISTRATION FEE ( Conference Early Registration (until 28 . 2 . 97) AU$ 300 ( Conference Registration (after 28 . 2 . 97) AU$ 350 ( Conference Early Registration for full-time student (until 28 . 2 . 97) AU$ 200 ( Conference Registration for full-time student (after 28 . 2 . 97) AU$ 250 ( Workshop Registration (AU$ 150 for one workshop) AU$ 150 ( Conference Dinner AU$ 65 ______________________________________________________________________ TOTAL AU$ _________ KES '97 REGISTRATION FORM Name: _______________________________________________ Title: ________________________________ Position: ________________ Organisation: _________________________________________________ Address: ________________________________________________________________________ ________________________________________________________________________ Tel: Fax: E-mail: PAYMENT DETAILS Please debit the following account in the amount of $_____________ ( Mastercard ( Bank card CARD NUMBER Expiry Date: Name of card holder __________________________________ Signature ______________________ OR . Please send cheque payable to: EASA Conference Account Conference Secretariat Knowledge - Based Intelligent Engineering Systems University of South Australia Adelaide, The Levels, S.A. 5095 Australia OR . Transfer the amount directly to the Bank Account Name: EASA Conference Account Account Number: 735 - 038 50 - 0833 Westpac Bank 56 O'Connel Street North Adelaide, S.A. 5006 Australia All participants are required to fill the registration form and register for this Conference. From Tony.Plate@Comp.VUW.AC.NZ Sat Nov 23 00:33:03 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 AAA01297 for ; Sat, 23 Nov 1996 00:32:56 -0600 Received: from TELNET-1.SRV.CS.CMU.EDU (TELNET-1.SRV.CS.CMU.EDU [128.2.254.108]) by lucy.cs.wisc.edu (8.7.6/8.7.3) with SMTP id AAA14235 for ; Sat, 23 Nov 1996 00:32:53 -0600 (CST) Received: from TELNET-1.SRV.CS.CMU.EDU by telnet-1.srv.cs.CMU.EDU id aa11744; 22 Nov 96 17:12:41 EST Received: from VIE.IUS.CS.CMU.EDU by TELNET-1.SRV.CS.CMU.EDU id aa11701; 22 Nov 96 16:42:57 EST Received: from VIE.IUS.CS.CMU.EDU by vie.ius.cs.cmu.edu id aa04678; 22 Nov 96 16:42 EST Received: from EDRC.CMU.EDU by B.GP.CS.CMU.EDU id aa02346; 21 Nov 96 19:39:33 EST Received: from kaukau.comp.vuw.ac.nz by EDRC.CMU.EDU id aa25136; 21 Nov 96 19:39:07 EST Received: from rialto.comp.vuw.ac.nz (rialto.comp.vuw.ac.nz [130.195.6.15]) by kaukau.comp.vuw.ac.nz (8.8.3/8.6.9-VUW) with ESMTP id NAA19878 for ; Fri, 22 Nov 1996 13:38:37 +1300 (NZDT) From: Tony Plate Received: from localhost (tap@localhost) by rialto.comp.vuw.ac.nz (8.8.3/8.7.3) with SMTP id NAA08761 for ; Fri, 22 Nov 1996 13:38:36 +1300 (NZDT) Message-Id: <199611220038.NAA08761@rialto.comp.vuw.ac.nz> X-Mailer: exmh version 1.6.5 12/11/95 To: Connectionists@CS.cmu.edu Subject: Faculty position Mime-Version: 1.0 Content-Type: text/plain; charset=us-ascii Date: Fri, 22 Nov 1996 13:38:36 +1300 Department of Computer Science Victoria University of Wellington LECTURESHIP in COMPUTER SCIENCE Position No: 634 November 1996 ---------------------------------------------------------------------------- The University invites applications from suitably qualified persons for a lectureship in Computer Science. Applicants should hold a PhD in computer science and show evidence of strong research potential and excellence in teaching. The Department is seeking to appoint within its established research areas of software engineering (including databases), concurrent and distributed systems, and artificial intelligence. The position is permanent, subject to a probationary period. Teaching programmes include the PhD, both research and professional Masters Degrees, and a BSc. The Department has 13 academic staff supported by 6 programming staff, 20-30 graduate students, and about 90 undergraduates per year. Further information about the Department is available at http://www.comp.vuw.ac.nz, or from the chairperson Peter.Andreae@vuw.ac.nz. Victoria University is situated in Wellington, the capital city of New Zealand. The city offers an outstanding combination of recreational and cultural activities. The University has an enrolment of about 10,000 and teaches comprehensive programmes in the sciences, arts, commerce, education, law and architecture. The salary scale for Lecturers is currently NZ$41,820-NZ$49,470 per annum, where there is a bar; then NZ$41.000-NZ$52,530 per annum. Enquiries and applications should be sent to the address below by the closing date of 30 January 1996. Applications should include the following: 1. name 2. address and telephone/fax numbers; email address if applicable 3. academic qualifications 4. present position 5. details of appointments held, with special reference to teaching appointments 6. research experience 7. field in which specially qualified 8. publications, prefarably under appropriate headings, eg, books, articles, monographs 9. names and addresses (fax numbers and/or email addresses if possible) of three persons from whom reference can be requested (in addition to naming referees, you can include recent testimonials if you wish) 10. date on which able to commence duties ---------------------------------------------------------------------------- In honouring the Treaty of Waitangi, the University welcomes applications from Tangata Whenua. It also welcomes applications from women, Pacific Island peoples, ethnic minorites, and people with disabilities. ---------------------------------------------------------------------------- Appointments Administrator Human Resources Directorate Victoria University of Wellington PO Box 600, Wellington New Zealand tel: +64 4 495-5272 fax: +64 4 495 5238 Peter.Gargiulo@vuw.ac.nz -------------