No subject

I found your commentary in the recent Connectionists posting very
interesting.  I have been working on the logical basis for neural
computation for well over a decade now and have what I feel are
many exciting results that I think help provide some focus
regarding how to approach the problem of the understanding and
designing artificial neural systems.  I have enclosed some
references -- not to impress you, but to give you a flavor for
the logical foundation that I have struggled with ultimately to
get it into an extremely simple and insightful explanation of
neural computation.

Anyway, I am very interested in what you talked about and am
interested in trying to attend the described panel. I think that
finally, researchers are beginning to ask the right questions.
I believe that learning itself is the computational search for
the "right" questions and so perhaps we collectively, are about
to really learn something about how the computational
objective(s) of the brain and neural computation in general.

    Sincerely,
     Prof. Robert L. Fry

Relevant Publication List

 "A logical basis for neural network design," invited book
chapter in Theory and application of neural networks, Academic
Press, to be published 1997.

 "Neural Mechanics," invited paper, Proc. Int. Conf. Neur. Info.
Proc., Hong Kong, 1996.

 "Rational neural models based on information theory," invited
paper, Post-conference workshop on Neural Information
Processing, NIPS'95.

 "Observer-participant models of neural processing," IEEE Trans.
Neural Networks, July 1995

 "Rational neural models based on information theory," 1995
Workshop on Maximum Entropy and Bayesian Methods, Sante Fe, NM,
July 1995, sponsored by the Sante Fe Institute and Lawrence
Livermore Laboratory

 "Rational neural models," Information theory and the brain
workshop, Stirling, Scotland, Sept 1995.

 "Neural processing of information," R. L. Fry, paper
presentation at 1994 IEEE International Symposium on
Information Theory, Norway.

 "A mathematical basis for an entropy machine that makes rational
decisions," APL Internal Memo F1F(1)90-U-094, 1990.

 "Neural models for the distributed processing of information,"
APL IRAD report,  1991.

 "The principle of cross-entropy applied to neural networks and
autonomous target recognition," APL Internal Memo F1F(1)90-U-005,
1990.

 "Maximized mutual information using macrocanonical probability
distributions," 1994 IEEE/IMS Workshop on Information Theory and
Statistics, Arlington, VA.

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