Workshop: What is inductive learning?
Lev Goldfarb
goldfarb at unb.ca
Fri Feb 16 13:30:54 EST 1996
Dear connectionists:
The following workshop should be of particular interest to the
connectionist community, since not only the topic itself was motivated by
the resent developments in cognitive science and AI as they are being
affected by connectionist movement, but also one of the main arguments
that is going to be presented at the workshop is that to capture
the main goals of the "connectionist movement" one needs to change
fundamentally the underlying architectures from the numeric to the
appropriately redefined "symbolic" architectures.
My apologies if you receive multiple copies of this message.
Please, post it.
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Call for extended abstracts:
WHAT IS INDUCTIVE LEARNING?
On the foundations of AI and Cognitive Science
Toronto - Canada
May 20 - 21, 1996
A workshop in conjunction with the 11th Biennial
Canadian AI Conference to be held at the Holiday
Inn on King, Toronto during 21 - 24 May 1996
This workshop is a long overdue attempt to look at the inductive learning
process (ILP) as the central process generating various representations of
objects (events).
To this end one needs, first of all, to have a working definition of the
ILP, which has been lacking. Here is a starting point: ILP is the process
that constructs class representation on the basis of a (small) finite set
of examples, i.e. it constructs the INDUCTIVE class representation. This
class representation must, in essence, provide INDUCTIVE definition (or
construction) of the class.
The constructed class representation, in turn, modifies the earlier
representation of the objects (within the context specified by the ILP).
Thus, any subsequent processes, e.g. pattern recognition, recall, problem
solving, are performed on the basis of the newly constructed object
(event) representations. To put it somewhat strongly, there are only
inductive representations.
Two main and strongly related reasons why ILPs have not been perceived as
the very central processes are a lack of their adequate understanding and
a lack of their satisfactory formal model. Most of the currently popular
formal models of ILPs (including connectionist models) do not provide
satisfactory inductive class representations. One can show that inductive
class representations (in other words, representations of concepts and
categories) cannot be adequately specified within the classical (numeric)
mathematical models.
We encourage all researchers (including graduate students) seriously
interested in the foundations of the above areas to participate in the
workshop. Both theoretical and applied contributions are welcomed
(including, of course, those related to vision, speech, and language).
While extended abstracts will be available at the workshop, we are
planning to publish the expanded and reviewed versions of the
presentations as a special issue of journal Pattern Recognition.
EXTENDED ABSTRACT SUBMISSION
----------------------------
Submit a copy (or e-mail version) of a 3-4 page extended abstract to
Lev Goldfarb
ILP Workshop Chair
Faculty of Computer Science
University of New Brunswick
P.O. Box 4400 E-mail: goldfarb at unb.ca
Fredericton, N.B. E3B 5A3 Tel: 506-453-4566
Canada Fax: 506-453-3566
E-mail submissions are encouraged.
Important dates:
----------------
Extended abstract due: Monday, March 25, 1996.
Notification & review back to the author: Friday April 5, 1996.
Final extended abstract due: Monday April 22, 1996.
For more information about the Canadian AI Conference which is held in
conjunction with two other conferences (Vision Interface and Graphics
Interface) see:
http://ai.iit.nrc.ca/cscsi/conferences/ai96.html
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-- Lev Goldfarb
http://wwwos2.cs.unb.ca/profs/goldfarb/goldfarb.htm
Please e-mail to me:
_____________________________________________________________________________
I intend to submit an abstract __
I plan to attend the workshop __
_____________________________________________________________________________
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