Boltzmann Machine learning using mean field theory ...

[Bert Kappen]

Dear Connectionists,

The following article

Boltzmann Machine learning using mean field 
theory and linear response correction 
written by Hilbert Kappen and Paco Rodrigues

Abstract: The learning process in Boltzmann Machines is computationally intractible. We present a new approximate learning algorithm for Boltzmann Machines, which is based on mean field theory and the linear response theorem. The computational complexity of the algorithm is cubic in the number of neurons.   In the absence of hidden units, we show how the weights can be directly computed from the fixed point equation of the learning rules. We show that the solution of this method is close to opti

which will apear in the proceedings NIPS of 1997 ed. Micheal Kearns
can now be downloaded from as ftp://ftp.mbfys.kun.nl/snn/pub/reports/Kappen.LR_NIPS.ps.Z

        Yours sincerely,
                        Hilbert Kappen

FTP INSTRUCTIONS

unix% ftp ftp.mbfys.kun.nl
Name: anonymous
Password: (use your e-mail address)
ftp> cd snn/pub/reports/
ftp> binary
ftp> get Kappen.LR_NIPS.ps.Z
ftp> bye
unix% uncompress Kappen.LR_NIPS.ps.Z
unix% lpr Kappen.LR_NIPS.ps