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A Parallelizable Algorithm for Orthogonally Constrained Optimization Problems

发布时间:2018-03-30 作者: 浏览次数:
Speaker: 刘歆 DateTime: 2018年4月13日(周五)上午11:00-12:00
Brief Introduction to Speaker:

刘歆,中科院数学与系统科学研究院,副研究员

Place: 六号楼二楼报告厅
Abstract:To construct a parallel approach for solving orthogonally constrained optimization problems is usually regarded as an extremely difficult mission, due to the low scalability of orthogonalization procedure. In this talk, we propose an infeasible algorithm for solving optimization problems with orthogonality constraints, in which orthogonalization is no longer needed at each iteration, and hence the algorithm can be parallelized. We also establish a global subsequence convergence and a worst-case complexity for our proposed algorithm. Numerical experiments illustrate that the new algorithm attains a good performance and a high scalability in solving discretized Kohn-Sham total energy minimization problems.
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