Prerequisites: 6.867, 6.041B, or 6.436, 18.06
Instructor: Professor Tamara Broderick (email@example.com)
Schedule: TR2:30-4, room 3-270
This subject counts as an Artificial Intelligence concentration subject.
This course will cover Bayesian modeling and inference at an advanced graduate level. Topics include de Finetti's theorem, decision theory, approximate inference (modern approaches and analysis of Monte Carlo, variational inference, etc), hierarchical modeling, (continuous and discrete) nonparametric Bayesian approaches, sensitivity and robustness, and evaluation.