Path: utzoo!utgpu!jarvis.csri.toronto.edu!mailrus!tut.cis.ohio-state.edu!ucbvax!ADS.COM!Vision-List-Request From: Vision-List-Request@ADS.COM (Vision-List moderator Phil Kahn) Newsgroups: comp.ai.vision Subject: Vision-List delayed redistribution Message-ID: <8902110123.AA00081@deimos.ads.com> Date: 11 Feb 89 01:04:04 GMT Sender: daemon@ucbvax.BERKELEY.EDU Reply-To: Vision-List@ADS.COM Distribution: inet Organization: The Internet Lines: 370 Approved: vision-list@ads.com Vision-List Digest Fri Feb 10 17:04:04 PDT 89 - Send submissions to Vision-List@ADS.COM - Send requests for list membership to Vision-List-Request@ADS.COM Today's Topics: What conferences and workshops should Vision List report? NIPS Call for Papers 6th International Workshop on Machine Learning Workshop on Models of Complex Human Learning ---------------------------------------------------------------------- Date: Fri, 10 Feb 89 17:07:12 EST From: Vision-List moderator Phil Kahn Subject: What conferences and workshops should Vision List report? If you've noticed, when there are several conference and workshop proceedings, I bundle them into a single List so regular postings aren't swamped. Hope this helps. Of the following three conferences and workshops, I only consider the NIPS conference to be of interest to the Vision List. The others I believe are more mainstream AI, and hence are not appropriate for the Vision List. Though I tend not to like editorially restricting submitted material, I favor eliminating conference, seminar, and workshop postings which do not bear a strong relationship to vision. This is just to let you know of this policy, since as the readership, this is your list. If you do not agree, please post your reasons to the List. I am trying to tighten the content to decrease clutter. In particular, I want to continue seeing more vision discussions and less peripheral postings. phil... ---------------------------------------------------------------------- Date: Thu, 9 Feb 89 13:16:17 EST From: jose@tractatus.bellcore.com (Stephen J Hanson) Subject: NIPS CALL FOR PAPERS IEEE Conference on Neural Information Processing Systems - Natural and Synthetic - Monday, November 27 -- Thursday November 30, 1989 Denver, Colorado This is the third meeting of a high quality, relatively small, inter-disciplinary conference which brings together neuroscientists, engineers, computer scientists, cognitive scientists, physicists, and mathematicians interested in all aspects of neural processing and computation. Several days of focussed workshops will follow at a nearby ski area. Major categories and examples of subcategories for papers are the following: [ 1. Neuroscience: ] Neurobiological models of development, cellular information processing, synaptic function, learning, and memory. Studies and analyses of neurobiological systems and development of neurophysiological recording tools. [ 2. Architecture Design: ] Design and evaluation of net architectures to perform cognitive or behavioral functions and to implement conventional algorithms. Data representation; static networks and dynamic networks that can process or generate pattern sequences. [ 3. Learning Theory: ] Models of learning; training paradigms for static and dynamic networks; analysis of capability, generalization, complexity, and scaling. [ 4. Applications: ] Applications to signal processing, vision, speech, motor control, robotics, knowledge representation, cognitive modelling and adaptive systems. [ 5. Implementation and Simulation: ] VLSI or optical implementations of hardware neural nets. Practical issues for simulations and simulation tools. Technical Program: Plenary, contributed, and poster sessions will be held. There will be no parallel sessions. The full text of presented papers will be published. Submission Procedures: Original research contributions are solicited, and will be refereed by experts in the respective disciplines. Authors should submit four copies of a 1000-word (or less) summary and four copies of a single-page 50-100 word abstract clearly stating their results by May 30, 1989. Indicate preference for oral or poster presentation and specify which of the above five broad categories and, if appropriate, sub-categories (for example, Learning Theory: Complexity , or Applications: Speech ) best applies to your paper. Indicate presentation preference and category information at the bottom of each abstract page and after each summary. Failure to do so will delay processing of your submission. Mail submissions to Kathie Hibbard, NIPS89 Local Committee, Engineering Center, Campus Box 425, Boulder, CO, 80309-0425. Organizing Committee Scott Kirkpatrick, IBM Research, General Chairman; Richard Lippmann, MIT Lincoln Labs, Program Chairman; Kristina Johnson, University of Colorado, Treasurer; Stephen J. Hanson, Bellcore, Publicity Chairman; David S. Touretzky, Carnegie-Mellon, Publications Chairman; Kathie Hibbard, University of Colorado, Local Arrangements; Alex Waibel, Carnegie-Mellon, Workshop Chairman; Howard Wachtel, University of Colorado, Workshop Local Arrangements; Edward C. Posner, Caltech, IEEE Liaison; James Bower, Caltech, Neurosciences Liaison; Larry Jackel, AT T Bell Labs, APS Liaison DEADLINE FOR SUMMARIES ABSTRACTS IS MAY 30, 1989 ---------------------------------------------------------------------- Date: Sat, 4 Feb 89 21:52:51 -0500 From: segre@gvax.cs.cornell.edu (Alberto M. Segre) Subject: 6th International Workshop on Machine Learning Organization: Cornell Univ. CS Dept, Ithaca NY Call for Papers: Sixth International Workshop on Machine Learning Cornell University Ithaca, New York; U.S.A. June 29 - July 1, 1989 The Sixth International Workshop on Machine Learning will be held at Cornell University from June 29 through July 1, 1989. The workshop will be divided into six parallel sessions, each focusing on a different theme: Combining Empirical and Explanation-Based Learning (M. Pazzani, chair). Both empirical evaluation and theoretical analysis have been used to identify the strengths and weaknesses of individual learning methods. Integrated approaches to learning have the potential of overcoming the limitations of individual methods. Papers are solicited exploring hybrid techniques involving, for example, explanation-based learning, case-based reasoning, constructive induction, or neural networks. Empirical Learning; Theory and Application (C. Sammut, chair). This session will be devoted to discussions on inductive (also called empirical) learning with particular emphasis on results that can be justified by theory or experimental evaluation. Papers should characterize methodologies (either formally or experimentally), their performance and/or problems for which they are well/ill suited. Comparative studies applying different methodologies to the same problem are also invited. Learning Plan Knowledge (S. Chien and G. DeJong, co-chairs). This session will explore machine learning of plan-related knowledge; specifically, learning to construct, index, and recognize plans by using explanation-based, empirical, case- based, analogical, and connectionist approaches. Knowledge-Base Refinement and Theory Revision (A. Ginsberg, chair). Knowledge-base refinement involves the discovery of plausible refinements to a knowledge base in order to improve the breadth and accuracy of the associated expert system. More generally, theory revision is concerned with systems that start out having some domain theory, but one that is incomplete and fallible. Two basic problems are how to use an imperfect theory to guide one in learning more about the domain as more experience accumulates, and how to use the knowledge so gained to revise the theory in appropriate ways. Incremental Learning (D. Fisher, chair, with J. Grefenstette, J. Schlimmer, R. Sutton, and P. Utgoff). Incremental learning requires continuous adaptation to the environment subject to performance constraints of timely response, environmental assumptions such as noise or concept drift, and knowledge base limitations. Papers that cross traditionally disparate paradigms are highly encouraged, notably rule-based, connectionist, and genetic learning; explanation-based and inductive learning; procedure and concept learning; psychological and computational theories of learning; and belief revision, bounded rationality, and learning. Representational Issues in Machine Learning (D. Subramanian, chair). This session will study representational practice in machine learning in order to understand the relationship between inference (inductive and deductive) and choice of representation. Present-day learners depend on careful vocabulary engineering for their success. What is the nature of the contribution representation makes to learning, and how can we make learners design/redesign hypotheses languages automatically? Papers are solicited in areas including, but not limited to, bias, representation change and reformulation, and knowledge-level analysis of learning algorithms. PARTICIPATION Each workshop session is limited to between 30 and 50 participants. In order to meet this size constraint, attendance at the workshop is by invitation only. If you are active in machine learning and you are interested in receiving an invitation, we encourage you to submit a short vita (including relevant publications) and a one-page research summary describing your recent work. Researchers interested in presenting their work at one of the sessions should submit an extended abstract (4 pages maximum) or a draft paper (12 pages maximum) describing their recent work in the area. Final papers will be included in the workshop proceedings, which will be distributed to all participants. SUBMISSION REQUIREMENTS Each submission (research summary, extended abstract, or draft paper) must be clearly marked with the author's name, affiliation, telephone number and Internet address. In addition, you should clearly indicate for which workshop session your submission is intended. Deadline for submission is March 1, 1989. Submissions should be mailed directly to: 6th International Workshop on Machine Learning Alberto Segre, Workshop Chair Department of Computer Science Upson Hall Cornell University Ithaca, NY 14853-7501 USA Telephone: (607) 255-9196 Internet: ml89@cs.cornell.edu While hardcopy submissions are preferred, electronic submissions will be accepted in TROFF (me or ms macros), LaTeX or plain TeX. Electronic submissions must consist of a single file. Be sure to include all necessary macros; it is the responsibility of the submitter to ensure his/her paper is printable without special handling. Foreign contributors may make special arrangements on an individual basis for sending their submissions via FAX. Submissions will be reviewed by the individual session chair(s). Determinations will be made by April 1, 1989. Attendance at the workshop is by invitation only; you must submit a paper, abstract or research summary in order to be considered. While you may make submissions to more than one workshop session, each participant will be invited to only one session. IMPORTANT DATES March 1, 1989 Submission deadline for research summaries, extended abstracts and draft papers. April 1, 1989 Invitations issued; presenters notified of acceptance. April 20, 1989 Final camera-ready copy of accepted papers due for inclusion in proceedings. ------------------------------ Date: Sat, 4 Feb 89 21:57:40 -0500 From: segre@gvax.cs.cornell.edu (Alberto M. Segre) Subject: Workshop on Models of Complex Human Learning Organization: Cornell Univ. CS Dept, Ithaca NY CALL FOR PARTICIPATION WORKSHOP ON MODELS OF COMPLEX HUMAN LEARNING Cornell University Ithaca, New York U.S.A. June 27-28, 1989 Sponsored by ONR Cognitive Science Branch This two-day workshop will bring together researchers whose learning research gives attention to human data and has implications for understanding human cognition. Of particular interest is learning research that relates to complex problem- solving tasks. There is an emphasis on symbol-level learning. The workshop will be limited to 30-50 attendees. Workshop presentations will be one hour in length, so as to allow in-depth presentation and discussion of recent research. Areas of interest include: Acquisition of Programming Skills Apprenticeship Learning Case Based Reasoning Explanation Based Learning Knowledge Acquisition Learning of Natural Concepts and Categories Learning of Problem Solving Skills Natural Language Acquisition Reasoning and Learning by Analogy The initial list of presenters is based on past proposals accepted by ONR. This call for papers solicits additional submissions. The current list of ONR-sponsored presenters includes: John Anderson (Carnegie Mellon) Tom Bever (Univ. of Rochester) Ken Forbus (Univ. of Illinois) Dedre Gentner (Univ. of Illinois) Chris Hammond (Univ. Chicago) Ryszard Michalski (George Mason Univ.) Stellan Ohlsson (Univ. of Pittsburgh) Kurt VanLehn (Carnegie Mellon) David Wilkins (Univ. of Illinois) SUBMISSIONS Presenters: Send four copies of (i) a previously published paper with a four page abstract that describes recent work or (ii) a draft paper. These materials will be used to select presenters; no workshop proceedings will appear. Please indicate whether you would consider being involved just as a participant. Participants: Send four copies of a short vitae that includes relevant publications, and a one-page description of relevant experience and projects. Submission Format: Hardcopy submissions are preferred, but electronic submissions will also be accepted in TROFF (ME or MS macros), LaTeX or plain TeX. Electronic submissions must consist of a single file that includes all the necessary macros and can be printed without special handling. Deadlines: All submissions should be received by the program chair by Tuesday, March 28, 1989; they will be acknowledged upon receipt. Notices of acceptance will be mailed by May 1, 1989. PROGRAM CHAIR David C. Wilkins Dept. of Computer Science University of Illinois 1304 West Springfield Ave Urbana, IL 61801 Telephone: (217) 333-2822 Internet: wilkins@m.cs.uiuc.edu ------------------------------ End of VISION-LIST ********************