报告题目：ARock: Asynchronous Parallel Coordinate Updatess

报告人：严明，密歇根州立大学

时  间：2016年7月19日    下午4:00-5:30

地  点：东区管理科研楼  数学科学学院1208室

内容提要：

We propose ARock, an asynchronous parallel algorithmic framework for finding a fixed point to a nonexpansive operator. In the framework, a set of agents (machines, processors, or cores) updates a sequence of randomly selected coordinates of the unknown variable in a parallel asynchronous fashion.

As special cases of ARock, novel algorithms in linear algebra, convex optimization, machine learning, distributed and decentralized optimization are introduced. We show that if the nonexpansive operator has a fixed point, then with probability one the sequence of points generated by ARock converges to a fixed point. Very encouraging numerical performance ofARock is observed on solving linear equations, sparse logistic regression, and other large-scale problems in recent data sciences.

报告人简介：

He is an Assistant Professor in the Department of Computational Mathematics, Science and Engineering (CMSE) and the Department of Mathematics at Michigan State University. He completed his PhD in Mathematics under the supervision of Professor Luminita A. Vese in the Department of Mathematics at University of California, Los Angeles in 2012. He has been working on optimization methods and their applications in sparse recovery and regularized inverse problems; variational methods for image processing and parallel and distributed algorithms for solving big data problems.