Computer Science 281B

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Title	Advanced Topics in Learning and Decision Making
Units	3
Prerequisites	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.

Sections Instructor Teaching Effectiveness How worthwhile was this course?

Spring 2006 Bartlett 5.4 / 7 ± 0.4
5.4 / 7 ± 0.5

Spring 2004 Jordan 6.3 / 7 ± 0.3
6.3 / 7 ± 0.3

Spring 2003 Bartlett 6.5 / 7 ± 0.5
6.2 / 7 ± 0.9

Spring 2001 Jordan 6.4 / 7 ± 0.3
6.2 / 7 ± 0.4

Overall Rating Teaching Effectiveness How worthwhile was this course?

Computer Science 281B 6.1 / 7 ± 0.1
6.0 / 7 ± 0.1

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