Linearized Alternating Direction Method of Multipliers for Constrained Linear Least-Squares Problem
Publication in refereed journal

香港中文大學研究人員

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摘要The alternating direction method of multipliers (ADMM) is applied to a constrained linear least-squares problem, where the objective function is a sum of two least-squares terms and there are box constraints. The original problem is decomposed into two easier least-squares subproblems at each iteration, and to speed up the inner iteration we linearize the relevant subproblem whenever it has no known closed-form solution. We prove the convergence of the resulting algorithm, and apply it to solve some image deblurring problems. Its efficiency is demonstrated, in comparison with Newton-type methods.
著者Chan RH, Tao M, Yuan XM
期刊名稱EAST ASIAN JOURNAL ON APPLIED MATHEMATICS
出版年份2012
月份11
日期1
卷號2
期次4
出版社GLOBAL SCIENCE PRESS
頁次326 - 341
國際標準期刊號2079-7362
電子國際標準期刊號2079-7370
語言英式英語
關鍵詞alternating direction method of multipliers; image processing; Linear least-squares problems; linearization
Web of Science 學科類別Mathematics; Mathematics, Applied

上次更新時間 2020-27-10 於 00:49