Workshop: Statistical Learning Theory: Lei

Speaker: Yunwen Lei, University of Hong Kong

Dates & times: December 5, 8, 9, 16, 2 – 4 pm AEDT

Location: The Quad Seminar Room S418 (McRae) A14.04.S418

Abstract: This workshop introduces fundamental tools in statistical learning theory to analyze the prediction behavior of machine learning algorithms. Topics include generalization analysis—such as population risk decomposition, uniform convergence, and Rademacher complexity—as well as the convergence analysis of optimization algorithms, including stochastic gradient descent and its early-stopping strategies. Applications to neural networks are also discussed.