Overview
Part I (120 m): Basic theory, models, and algorithms
Basics of Bayesian methods
Regularized Bayesian inference and examples
Part II (60 m): Scalable Bayesian methods
Online learning
Large-scale topic graph learning and visualization
Part III (20 m): Q&A
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