Machine Learning List Vol. 2 No. 17

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Machine Learning List

 · 11 months ago

 
		 Machine Learning List: Vol. 2 No. 17 
			 Sunday, Sept 9, 1990 

Contents: 
	1991 Machine Learning Workshop 
	m-out-of-n concepts 

 
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------------------------------ 
From: Lawrence Birnbaum <birnbaum@fido.ils.nwu.edu> 
Subject: ML91 -- THE EIGHTH INTERNATIONAL WORKSHOP ON MACHINE LEARNING 

 
        ML91 -- THE EIGHTH INTERNATIONAL WORKSHOP ON MACHINE LEARNING 

         CALL FOR WORKSHOP PROPOSALS AND PRELIMINARY CALL FOR PAPERS 

 
On behalf of the organizing committee, we are pleased to solicit proposals for 
the workshops that will constitute ML91, the Eighth International Workshop on 
Machine Learning, to be held in late June, 1991, at Northwestern University, 
Evanston, Illinois, USA.  We anticipate choosing six workshops to be held in 
parallel over the three days of the meeting.  Our goal in evaluating workshop 
proposals is to ensure high quality and broad coverage of work in machine 
learning.  Workshop committees -- which will operate for the most part 
independently in selecting work to be presented at ML91 -- should include two 
to four people, preferably at different institutions.  The organizing 
committee may select some workshops as proposed, or may suggest changes or 
combinations of proposals in order to achieve the goals of quality and 
balance. 

Proposals are due October 10, 1990, preferably by email to: 

        ml91@ils.nwu.edu 

although hardcopy may also be sent to the following address: 

        ML91 
        Northwestern University 
        The Institute for the Learning Sciences 
        1890 Maple Avenue 
        Evanston, IL 60201  USA 

        fax (708) 491-5258 

Please include the following information: 

        1. Workshop topic 
        2. Names, addresses, and positions of workshop committee members 
        3. Brief description of topic 
        4. Workshop format 
        5. Justification for workshop, including assessment of breadth of 
           appeal 

Workshop format is somewhat flexible, and may include invited talks, panel 
discussions, short presentations, and even small working group meetings. 
However, it is expected that the majority of time will be devoted to technical 
presentations of 20 to 30 minutes in length, and we encourage the inclusion of 
a poster session in each workshop.  Each workshop will be allocated 
approximately 100 pages in the Proceedings, and papers to be published must 
have a minimum length of (most likely) 4 to 5 pages in double column format. 
Workshop committee members should be aware of these space limitations in 
designing their workshops. 

We encourage proposals in all areas of machine learning, including induction, 
explanation-based learning, connectionist and neural net models, adaptive 
control, pattern recognition, computational models of human learning, 
perceptual learning, genetic algorithms, computational approaches to teaching 
informed by learning theories, scientific theory formation, etc.  Proposals 
centered around research problems that can fruitfully be addressed from a 
variety of perspectives are particularly welcome. 

The workshops to be held at ML91 will be announced towards the end of October. 
In the meantime, we would like to announce a preliminary call for papers; the 
submission deadline is February 1, 1990.  Authors should bear in mind the 
space limitations described above. 

On behalf of the organizing committee, 

        Larry Birnbaum 
        Gregg Collins 

        Program co-chairs, ML91 

(This announcement is being sent/posted to ML-LIST, CONNECTIONISTS, ALife, 
PSYCOLOQUY, NEWS.ANNOUNCE.CONFERENCES, COMP.AI, COMP.AI.EDU, 
COMP.AI.NEURAL-NETS, COMP.ROBOTICS, and SCI.PSYCHOLOGY.  We encourage readers 
to forward it to any other relevant mailing list or bulletin board.) 

------------------------------ 
Subject: m-out-of-n concepts 
From: Michael Pazzani <pazzani@ICS.UCI.EDU> 

Can anyone provide pointers to learning m-out-of-n concepts. 
Such concepts have natural applications in medicine and in  
prototype representations of concepts.  For examples, 

2-out-of-4(A,B,C,D) = AB + AC + AD + BC + BD + CD 

 
I'm aware that perceptions can represent and learn such concepts, 
and of Spackman's 1988 MLC paper.  Has any additional work been 
reported in this area? 

Thanks 
Mike 

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END of ML-LIST 2.17