Catalog 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.

Units: 3

Also Offered As: STAT C241B

Related Areas:

• Artificial Intelligence (AI)

Formats:
Spring: 3 hours of lecture per week
Fall: 3 hours of lecture per week

Grading Basis: letter

Final Exam Status: No final exam

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Class Schedule (Spring 2025):
CS C281B – TuTh 12:30-13:59, Cory 521 – Benjamin Recht

Class homepage on inst.eecs

Links:

• CS enrollment policies
• EE enrollment policies
• HKN course maps