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數學系seminar 塊對稱高斯-塞得分解定理在凸二次規劃中的應用

創建時間:  2020/09/09  龔惠英   瀏覽次數:   返回

    上海大學運籌與優化開放實驗室國際科研合作平臺系列報告

報告主題:A block symmetric Gauss-Seidel decomposition theorem for convex quadratic programming and its applications (塊對稱高斯-塞得分解定理在凸二次規劃中的應用)

報告人:Kim-Chuan Toh 教授(新加坡國立大學數學系)

報告時間:2020年9月21日(周一) 14:00-16:00

參會方式:騰訊 會議

會議ID:302 840 008

會議密碼:200921

會議鏈接:https://meeting.tencent.com/s/Xbk2rAnqeKOE

主辦部門:上海大學運籌與優化開放實驗室-國際科研合作平臺、上海市運籌學會、上海大學理學院數學系

報告摘要:For a multi-block convex composite quadratic programming (CCQP) with an additional nonsmooth term in the first block, we present a block symmetric Gauss-Seidel (sGS) decomposition theorem, which states that each cycle of the block sGS method is equivalent to solving the CCQP with an additional proximal term constructed from the sGS decomposition of the quadratic term. As a basic building block, the sGS decomposition theorem has played a key role in various recently developed algorithms such as the inexact proximal ALM/ADMM for linearly constrained multi-block convex composite conic programming. We demonstrate how our sGS-based ADMM can be applied to solve doubly nonnegative semidefinite programming and Wasserstein barycenter problems.


歡迎教師、學生參加!

上一條:硬X射線吸收譜簡介及在催化領域應用介紹

下一條:數學系“60周年”系慶系列報告 來自于應用的若干圖論相關問題


數學系seminar 塊對稱高斯-塞得分解定理在凸二次規劃中的應用

創建時間:  2020/09/09  龔惠英   瀏覽次數:   返回

    上海大學運籌與優化開放實驗室國際科研合作平臺系列報告

報告主題:A block symmetric Gauss-Seidel decomposition theorem for convex quadratic programming and its applications (塊對稱高斯-塞得分解定理在凸二次規劃中的應用)

報告人:Kim-Chuan Toh 教授(新加坡國立大學數學系)

報告時間:2020年9月21日(周一) 14:00-16:00

參會方式:騰訊 會議

會議ID:302 840 008

會議密碼:200921

會議鏈接:https://meeting.tencent.com/s/Xbk2rAnqeKOE

主辦部門:上海大學運籌與優化開放實驗室-國際科研合作平臺、上海市運籌學會、上海大學理學院數學系

報告摘要:For a multi-block convex composite quadratic programming (CCQP) with an additional nonsmooth term in the first block, we present a block symmetric Gauss-Seidel (sGS) decomposition theorem, which states that each cycle of the block sGS method is equivalent to solving the CCQP with an additional proximal term constructed from the sGS decomposition of the quadratic term. As a basic building block, the sGS decomposition theorem has played a key role in various recently developed algorithms such as the inexact proximal ALM/ADMM for linearly constrained multi-block convex composite conic programming. We demonstrate how our sGS-based ADMM can be applied to solve doubly nonnegative semidefinite programming and Wasserstein barycenter problems.


歡迎教師、學生參加!

上一條:硬X射線吸收譜簡介及在催化領域應用介紹

下一條:數學系“60周年”系慶系列報告 來自于應用的若干圖論相關問題

江苏快三