報(bào)告承辦單位:數(shù)學(xué)與統(tǒng)計(jì)學(xué)院

報(bào)告題目: Proximal Algorithm for Two-block Nonsmooth and Nonconvex Optimization Problems and Its Application in the Design of Sparse-enhanced Control

報(bào)告人姓名: Wah June Leong

報(bào)告人所在單位: 馬來西亞博特拉大學(xué)

報(bào)告人職稱/職務(wù)及學(xué)術(shù)頭銜:副教授/博導(dǎo)

報(bào)告時(shí)間:2019年4月12日，10:00—11:00

報(bào)告地點(diǎn):  金盆嶺1A－406

報(bào)告人簡(jiǎn)介: Wah June Leong，馬來西亞博特拉大學(xué)副教授，于2003年在馬來西亞博特拉大學(xué)獲得博士學(xué)位，2008-2009年在中國(guó)科學(xué)院數(shù)學(xué)與系統(tǒng)科學(xué)研究所進(jìn)行博士后研究，合作導(dǎo)師戴彧虹研究員。2015-2018年期間先后訪問澳大利亞科廷大學(xué)、首爾大學(xué)、重慶師范大學(xué)、東北大學(xué)、以及中國(guó)科學(xué)院。Wah June Leong老師研究的主要方向?yàn)榇笠?guī)模優(yōu)化問題的數(shù)值算法以及帶非光滑優(yōu)化的最優(yōu)控制問題，已發(fā)表論文80余篇，主持馬來西亞教育部和科技部項(xiàng)目6項(xiàng)，指導(dǎo)博士后2名，培養(yǎng)博士和碩士研究生15名。

報(bào)告摘要：This talk begins by introducing a proximal alternating linearized minimization algorithm for solving a broad class of nonsmooth and nonconvex minimization problems. Building on the Kurdyka-Lojasiewicz property, we derive a convergence analysis framework and establish that each bounded sequence generated by the algorithm converges to a critical point of the problem. As an illustration of the results, we give a formulation to design controllers of linear–quadratic regulator (LQR) control systems that can provide a desired trade-off between the system performance and the sparsity of the feedback matrix. The model formulation that involves nonsmooth-nonconvex l0-norm minimization problem is then solved by using our proximal algorithm.