应002资讯网孙杰宝的邀请，清华大学史作强副教授来访并做学术报告，欢迎感兴趣的师生参加。

报告题目：Understanding Machine Learning from Partial Differential Equation

报告时间：2019年4月14日9:00-11:30

报告摘要：In this talk, I will present several PDE models and show their relations to machine learning and deep learning problem. In these PDE models, we use manifold to model the low dimensional structure hidden in high dimensional data and use PDEs to study the manifold. I will reveal the close connections between PDEs and deep neural networks. Theoretical analysis and numerical simulations show that PDEs provide us powerful tools to understand high dimensional data.

报告地点：格物楼503

报告人简介：史作强，清华大学丘成桐数学科学中心，数学科学系副教授，曾在美国加州理工学院应用与计算数学系做博士后，主要研究方向为偏微分方程数值方法，图像处理和机器学习中的偏微分方程模型，非线性非平稳信号时频分析等，已在Advances in Mathematics 、Archive for Rational Mechanics and Analysis、Communications in Mathematical Sciences、SIAM Journal on Imaging Sciences等学术期刊上发表学术论文30余篇。