HKU HKU Dept of Statistics & Actuarial Science, HKU

Seminar by Dr. Pengkun YANG from Tsinghua University

DateOctober 20, 2021, Wednesday
Time2:30 p.m. - 3:30 p.m.
Venuevia Zoom
TitleLearning overparametrized neural networks & statistical models

Modern machine learning has constantly presented puzzling empirical properties and surprised the classical statistical theory. Learning with overparametrized models is becoming a norm in data-analytic applications, and the tension of memorization rarely bothers practitioners.

In this talk, I will discuss the training of overparametrized neural networks from both the neural tangent kernel and the mean-field perspectives, which guarantees the global convergence property despite the non-convexity of the optimization landscape. I will also discuss more interesting phenomena in a series of overparametrized statistical questions.

About the speaker

Dr. Pengkun Yang current is an assistant professor at the Center for Statistical Science, Tsinghua University. He received his PhD in Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, and was a Postdoc fellow at Princeton University. His research areas include theory and algorithms for high-dimensional statistics, mathematical data science, statistical machine learning, and optimization. He has published several papers at top statistical journals and top machine learning conferences.