報告題目：Understanding Surprising Generalization Phenomena in Deep Learning

報告時間：2023年12月25日14:30

報告地點：437bwin必贏國際官網B404會議室

報告人：胡威

報告人國籍：中國

報告人單位：密歇根大學計算機科學與工程系

報告人簡介：Wei Hu is an Assistant Professor in Computer Science and Engineering at the University of Michigan. He obtained his Ph.D. degree from Princeton University and Bachelor's degree from Tsinghua University. His research interest is in the theoretical and scientific foundations of deep learning. He is a recipient of the Google Research Scholar award and the Siebel Scholarship.

報告摘要：Despite the phenomenal empirical successes of deep learning in many application domains, its underlying mathematical mechanisms remain poorly understood. In particular, deep learning has exhibited a number of surprising generalization phenomena that are not captured by classical statistical learning theory. This talk will introduce some of the intriguing generalization phenomena observed in deep learning, including implicit regularization, benign overfitting, and grokking, as well as some recent progress on the theoretical characterizations of these phenomena.

邀請人：王勝