New probabilistic inference algorithms that harness the strengths of variational and Monte Carlo methods

The central objective of this thesis is to develop new algorithms for inference in probabilistic graphical models that improve upon the state-of-the-art and lend new insight into the computational nature of probabilistic inference. The four main technical contributions of this thesis are: 1) a new f...

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Bibliographic Details
Main Author: Carbonetto, Peter
Format: Others
Language:English
Published: University of British Columbia 2009
Online Access:http://hdl.handle.net/2429/11990