CS C281B. Advanced Topics in Learning and Decision Making
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
Formats:
Spring: 3 hours of lecture per week
Fall: 3 hours of lecture per week
Grading basis: letter
Final exam status: No final exam
Also listed as: STAT C241B
Class Schedule (Spring 2025):
CS C281B – MoWe 12:30-13:59, Soda 306 –
Benjamin Recht
Related Areas: