Date: 10 Feb 89 17:04:04-PST
From: Vision-List moderator Phil Kahn <Vision-List-Request@ADS.COM>
Errors-to: Vision-List-Request@ADS.COM
Reply-to: Vision-List@ADS.COM
Subject: Vision-List delayed redistribution
To: 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

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Date: Fri, 10 Feb 89 17:07:12 EST
From: Vision-List moderator Phil Kahn <Vision-List-Request@ADS.COM>
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...


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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  
 

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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
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