Algebraic Geometry of the Restricted Boltzmann Machine

Time

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Locations

Siegal Hall, Room 118

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Host

Department of Applied Mathematics

 

 

Speaker

Jason Morton
Department of Mathematics, Pennsylvania State University

 

 

 

 

 

Description

 

 

 

 

The restricted Boltzmann machine was the original building block of deep learning models.  An implicit description of the set of probability distributions it can represent is very difficult, and is unknown even in the smallest nontrivial case.  However there are aspects of the RBM's algebraic geometry which are accessible.  We discuss a series of four papers on the geometry of RBMs leading to, among other things, a proof that the RBM always has the expected dimension: in other words, it doesn't waste parameters.

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