Statistical Machine Learning CMPT 727 (3)
Statistical foundation for machine learning algorithms, emphasizing bias-variance tradeoff. Students will learn principles for choosing effective methods and tailoring them to fit a given learning problem. Potential topics include probabilistic graphical models, maximum likelihood estimation, latent variables and the EM algorithm, convex optimization, and variational and sampling-based methods.
Tu 11:30 AM – 12:20 PM
Th 9:30 AM – 11:20 AM
AQ 3153, Burnaby
AQ 3159, Burnaby