Hector Sussmann to speak on formal analysis of Boltzmann Machine Learning

[Lorien Y. Pratt]

				 Fall, 1988  
		     Neural Networks Colloquium Series 
				 at Rutgers  

	       On the theory of Boltzmann Machine Learning
	       -------------------------------------------

			      Hector Sussmann
		Rutgers University Mathematics Department

		    Room 705 Hill center, Busch Campus  
		    Friday October 14, 1988 at 11:10 am 
		    Refreshments served before the talk

				 Abstract   

The Boltzmann machine is an algorithm for learning in neural networks,
involving alternation between a ``learning'' and ``hallucinating'' phase.
In this talk, I will present a Boltzmann machine algorithm for which it
can be proven that, for suitable choices of the parameters, the weights
converge so that the Boltzmann machine correctly classifies all
training data.  This is because the evolution of the weights follow
very closely, with very high probability, an integral trajectory of the
gradient of the likelihood function whose global maxima are exactly the
desired weight patterns.