数学科学学院

Parallelizable Algorithms for Optimization Problems with Orthogonality Constraints

来源:数学科学学院 发布时间:2018-11-26   662

题目:Parallelizable Algorithms for Optimization Problems with Orthogonality Constraints

报告人:刘歆(中国科学院数学与系统科学研究所)

时间:11月27日 下午16:00-17:00

地点:逸夫工商楼105

摘要:To construct a parallel approach for solving optimization problems with orthogonality constraints is usually regarded as an extremely difficult mission, due to the low scalability of the orthogonalization procedure. However, such demand is particularly huge in some application domains such as material computation. In this talk, we propose two infeasible algorithms,  based on augmented Lagrangian penalty function, for solving optimization problems with orthogonality constraints. Different with the classic augmented Lagrangian method, our algorithms update both the prime variables and the dual variables by new strategies. The orthogonalization procedure is only invoked once as the last step of the above mentioned two algorithms. Consequently, the main parts of these two algorithms can be parallelized naturally. We establish global subsequence convergence results for our proposed algorithms. Worst-case complexity and local convergence rate are also studied under some mild assumptions. Numerical experiments, including tests under parallel environment, illustrate that our new algorithms attain good performances and a high scalability in solving discretized Kohn-Sham total energy minimization problems. 

联系人:赖俊 laijun6@zju.edu.cn

Copyright © 2023 浙江大学数学科学学院    版权所有

    浙ICP备05074421号

技术支持: 创高软件     管理登录

    您是第 1000 位访问者