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(from the 2011-2013 General Catalog updated as of  May 16, 2013)
Advanced Topics in Learning and Decision Making  --  Computer Science (Engineering) (COMPSCI) C281B [3 units]
Course Format: Three hours of lecture per week.
Prerequisites: Computer Science C281A/Statistics C241A.
Description: Recent topics include: Graphical models and approximate inference algorithms. Markov chain Monte Carlo, mean field and probability propagation methods. Model selection and stochastic realization. Bayesian information theoretic and structural risk minimization approaches. Markov decision processes and partially observable Markov decision processes. Reinforcement learning. Also listed as Statistics C241B.
(SP) Bartlett, Jordan, Wainwright
 
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