Theoretical study on deep learning:approximation,generalization and generation


题目:Theoretical study on deep learning:approximation,generalization and generation






地点:Zoom会议会议号:876 0592 8254密码:2023


摘要:In the first part of this talk, I will discuss some theoretical studies on deeplearning with a focus on approximation, generalization. In particular, I willcover error analysis with over-parameterization. In the second part, I will delveinto the concept of Gaussian stochastic interpolations and their applications,including the derivation of functional inequality with dimension-free constantsas well as sampling and generative learning.

报告人简介:Dr. Yuling Jiao is an Associate Professor in the School of Mathematicsand Statistics in Wuhan University. His research interests include machineearning, scientific computing. His research works were published in the Annalsof Statistics, Journal of the American Statistical Association, Statistical Science!A Review Journal ofIMS, SIAM Journal on Mathematical Analysis, SIAMournal on Numerical Analysis, SIAM Journal on Scientific Computing, Appliecand Computational Harmonic Analysis. Inverse Problems, IEEE Transactions onSignal Processing. Journal of Machine Learning Research, ICML . NeurIPS.


Copyright (C)2023 哈尔滨工业大学数学研究院版权所有
电话:86413107      邮箱