Paper available: "A mean field approach to Bayes Learning in feed-forward neural networks"

[Ole Winther]

FTP-host: connect.nbi.dk
FTP-file: neuroprose/opper.bayes.ps.Z
WWW-host: http://connect.nbi.dk

----------------------------------------------

The following paper is now available:

A mean field approach to Bayes Learning in feed-forward neural networks
[12 pages]

Manfred Opper
Theoretical Physics, University of Wurzburg, Germany

Ole Winther
CONNECT, The Niels Bohr Institute, University of Copenhagen, Denmark

Abstract:
We propose an algorithm to realise Bayes optimal predictions for feed-forward
neural networks which is based on the TAP mean field method developed for the
statistical mechanics of disordered systems. We conjecture that our approach
will be exact in the thermodynamic limit. The algorithm results in a simple
built-in leave-one-out crossvalidation of the predictions. Simulations for the
case of the simple perceptron and the committee machine are in excellent
agreement with the results of replica theory.

Please do not reply directly to this message.

-----------------------------------------------

FTP-instructions:

unix> ftp connect.nbi.dk (or 130.225.212.30)
ftp> Name: anonymous
ftp> Password: your e-mail address
ftp> cd neuroprose
ftp> binary
ftp> get opper.bayes.ps.Z
ftp> quit
unix> uncompress opper.bayes.ps.Z

-----------------------------------------------

Ole Winther,
Computational Neural Network Center (CONNECT)
Niels Bohr Institute
Blegdamsvej 17
2100 Copenhagen
Denmark

Telephone: +45-3532-5200
Direct:    +45-3532-5311
Fax:       +45-3142-1016
e-mail:    winther at connect.nbi.dk