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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| Language: | English |
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University of British Columbia
2009
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| Online Access: | http://hdl.handle.net/2429/11990 |