报告题目：Stochastic Gradient Descent for Inverse Problems

报告时间：2021年4月8日，上午10:00

报告摘要：

In this talk, I will discuss the stochastic gradient descent for solving linear and nonlinear inverse problems. Such algorithms have been very popular in a number of practical inverse problems. However, the relevant mathematical theory in the context of ill-posed inverse problems remains largely missing. In this talk, I will present some recent theoretical results, and illustrate the theory with numerical examples.

报告人简历：

Dr. Bangti Jin (金邦梯) is Professor of Inverse Problems at the Department of Computer Science, University College London. He received his PhD in Mathematics from the Chinese University of Hong Kong, Hong Kong, in 2008. Previously, he was Assistant Professor of Mathematics at University of California, Riverside (2013–2014), Visiting Assistant Professor at Texas A&M University (2010–2013), Alexandre von Humboldt Postdoctoral Researcher at the University of Bremen (2009–2010). His research interests include inverse problems, numerical analysis and data-driven techniques, and serves on the editorial board of several journals, including Inverse Problems, Advances in Computational Mathematics and Journal of Computational Mathematics etc.

腾讯会议信息：

会议时间：2021/04/08 10:00-11:30 (GMT+08:00) 中国标准时间 - 北京

点击链接入会，或添加至会议列表：

https://meeting.tencent.com/s/N4oaCJhjXnka

会议 ID：957 548 144