Statistical Physics of Neural Networks: Preprints available via ftp

[Prof. Jong-Hoon Oh]

Dear Colleagues,

Preprints to be published in the proceedings of NNSMP95 (Neural Networks:
The Statistical Mechanics Perspective) are available.

Here is the table of contents for NNSMP95 Proceedings.
It is available via anonymous ftp at tico.postech.ac.kr
in the pub/NNSMP/proceedings95.

For accompanying mailing list service, please read README file.

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Jong-Hoon Oh
Associate Professor, Department of Physics        jhoh at vision.postech.ac.kr
Pohang Institute of Science Technology            Tel) +82-562-2792069
Hyoja San 31 Pohang, 790-784 Kyoungbuk, Korea     Fax) +82-562-2793099
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-----------------Table of Contents - LaTeX format --------------------------

\documentstyle[12pt]{article}
\begin{document}
\centerline{\Large\bf Table of Contents}
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Preface

\bigskip
{\bf Part I. Learning Curves}

\begin{itemize}

\item Statistical Theory of Learning Curves

S. Amari, N. Murata and K. Ikeda.

\item Generalization in Two-Layer Neural Networks

J.-H. Oh, K. Kang, C. Kwon and Y. Park

\item Annealed Theories of Learning

H. S. Seung

\item Mutual Information and Bayes Methods
for Learning a Distribution

D. Haussler and M. Opper

\item General Bounds for Predictive Errors in Supervised Learning

M. Opper and D. Haussler

\item  Perceptron Learning: The Largest Version Space

M. Biehl and M. Opper

\item Large Scale Simulations for Learning Curves

K.-R. M\"uller, M. Finke, N. Murata and S. Amari

\item Geometry of Admissible Parameter Region
in Neural Learning

K. Ikeda and S. Amari

\item Learning by a Population of Perceptrons

K. Kang, J.-H. Oh and C. Kwon

\end{itemize}

{\bf Part II. Dynamics}

\begin{itemize}

\item On-Line Learning of Dichotomies:
Algorithms and Learning Curves

H. Sompolinsky, N. Barkai and H. S. Seung

\item The Bit-Generator and Time-Series Prediction

E. Eisenstein, I. Kanter,  D. A. Kessler and W. Kinzel

\item Phase Dynamics of Two and Three Coupled Hodgkin-Huxley Neurons
under DC Currents

S. Kim, S. G. Lee, H. Kook and J. H. Shin

\item Periodic Synchronization in Networks of Neuronal Oscillators

M. Y. Choi

\item Synchronization in Neural Networks with Finite Storage Capacity

K. Park and M. Y. Choi

\end{itemize}

{\bf Part III. Associative Memory and Other Topics}

\begin{itemize}

\item The Cavity Method: Applications to Learning
and Retrieval in Neural Networks

K. Y. M. Wong

\item Storage Capacity of a Fully Connected Committee Machine

C. Kwon, Y. Park and J.-H. Oh

\item Thermodynamic Properties of the Multi-Neuron Interaction Model
without Truncating the Interaction

D.~Boll\'e, J.~Huyghebaert and G.~M.~Shim

\item Symmetry between Neuronal and Synaptic Dynamics of Neural Net

H.-F. Yanai

\item Learning and Maximum Entropy
in General Boltzmann Machines

C. Hicks and H. Ogawa

\item On the (Free) Energy of Stochastic and Continuous Hopfield Neural Networks

J. van den Berg and J. C. Bioch

\item Neural Thermodynamics for Biological Ensembles

A. Coster

\end{itemize}

{\bf Part IV. Applications}

\begin{itemize}

\item Learning Algorithms for Classification: A Comparison on Handwritten Digit
Recognition

Y. LeCun, L. D. Jackel, L. Bottou, C. Cortes, J. S. Denker, H. Drucker,
I. Guyon, U. A. M\"uller, E. S\"ackinger, P. Simard and V. Vapnik

\item On the Consequences of the Statistical Mechanics Theory of Learning
Curves
for the Model Selection Problem

M. J. Kearns

\item Learning of a Two-Layer Neural Network with Flexible Hidden
Layer Size

J. Kim, K. Kang and J.-H. Oh

\item Distributed Population Representation in Proprioceptive Cortex

S. Cho, M. Jang and J. A. Reggia

\item Designing Cost Functions for Additional Network Functionality

S. Y. Lee

\item Self-Organization of Gaussian Mixture Model for PDF Estimation

S. Lee and S. Shimoji



\end{itemize}
\end{document}


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Jong-Hoon Oh
Associate Professor, Department of Physics        jhoh at vision.postech.ac.kr
Pohang Institute of Science Technology            Tel) +82-562-2792069
Hyoja San 31 Pohang, 790-784 Kyoungbuk, Korea     Fax) +82-562-2793099
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