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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.

Section Instructor Day/Time Location
Maxwell Libbrecht
Jan 10 – Apr 11, 2022: Mon, 10:30–11:20 a.m.
Jan 10 – Apr 11, 2022: Thu, 10:30 a.m.–12:20 p.m.
Burnaby
Burnaby