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An Accelerated Proximal Gradient Algorithm for Hankel Tensor Completion
《Journal of the Operations Research Society of China》2024年第2期461-477,共17页Chuan-Long Wang Xiong-Wei Guo Xi-Hong Yan 
In this paper,an accelerated proximal gradient algorithm is proposed for Hankel tensor completion problems.In our method,the iterative completion tensors generated by the new algorithm keep Hankel structure based on p...
关键词：Hankel tensor Tensor completion Accelerated proximal gradient algorithm 
Accelerated Stochastic Peaceman–Rachford Method for Empirical Risk Minimization
《Journal of the Operations Research Society of China》2023年第4期783-807,共25页Jian-Chao Bai Feng-Miao Bian Xiao-Kai Chang Lin Du 
supported by the National Natural Science Foundation of China(Nos.12001430,11972292 and 12161053);the China Postdoctoral Science Foundation(No.2020M683545);the Guangdong Basic and Applied Basic Research Foundation(No.2023A1515012405).
This work is devoted to studying an accelerated stochastic Peaceman–Rachford splitting method(AS-PRSM)for solving a family of structural empirical risk minimization problems.The objective function to be optimized is ...
关键词：Empirical risk minimization Convex optimization Stochastic Peaceman-Rachford method Indefinite proximal term Complexity 
A Mini-Batch Proximal Stochastic Recursive Gradient Algorithm with Diagonal Barzilai–Borwein Stepsize被引量：1
《Journal of the Operations Research Society of China》2023年第2期277-307,共31页Teng-Teng Yu Xin-Wei Liu Yu-Hong Dai Jie Sun 
the National Natural Science Foundation of China(Nos.11671116,11701137,12071108,11991020,11991021 and 12021001);the Major Research Plan of the NSFC(No.91630202);the Strategic Priority Research Program of Chinese Academy of Sciences(No.XDA27000000);the Natural Science Foundation of Hebei Province(No.A2021202010)。
Many machine learning problems can be formulated as minimizing the sum of a function and a non-smooth regularization term.Proximal stochastic gradient methods are popular for solving such composite optimization proble...
关键词：Stochastic recursive gradient Proximal gradient algorithm Barzilai-Borwein method Composite optimization 
Randomized Primal–Dual Proximal Block Coordinate Updates被引量：2
《Journal of the Operations Research Society of China》2019年第2期205-250,共46页Xiang Gao Yang-Yang Xu Shu-Zhong Zhang 
This work is partly supported by the National Science Foundation(Nos.DMS-1719549 and CMMI-1462408).
In this paper,we propose a randomized primal–dual proximal block coordinate updating framework for a general multi-block convex optimization model with coupled objective function and linear constraints.Assuming mere ...
关键词：Primal-dual method Alternating direction method of multipliers(ADMM) Randomized algorithm Iteration complexity·First-order stochastic approximation 
An LQP-Based Symmetric Alternating Direction Method of Multipliers with Larger Step Sizes被引量：4
《Journal of the Operations Research Society of China》2019年第2期365-383,共19页Zhong-Ming Wu Min Li 
This research was supported by National Natural Science Foundation of China Grant 11771078;Natural Science Foundation of Jiangsu Province Grant BK20181258;Project of 333 of Jiangsu Province Grant BRA2018351;Postgraduate Research&Practice Innovation Program of Jiangsu Province Grant KYCX18_0200.
Symmetric alternating directionmethod of multipliers(ADMM)is an efficient method for solving a class of separable convex optimization problems.This method updates the Lagrange multiplier twice with appropriate step si...
关键词：Convex optimization Symmetric alternating direction method of multipliers Logarithmic-quadratic proximal regularization Larger step sizes Global convergence 
On Globally Q-Linear Convergence of a Splitting Method for Group Lasso
《Journal of the Operations Research Society of China》2018年第3期445-454,共10页Yun-Da Dong Hai-Bin Zhang Huan Gao 
This research was supported by the National Natural Science Foundation of China(No.61179033);Collaborative Innovation Center on Beijing Society-Building and Social Governance.
In this paper,we discuss a splitting method for group Lasso.By assuming that the sequence of the step lengths has positive lower bound and positive upper bound(unrelated to the given problem data),we prove its Q-linea...
关键词：Group Lasso Splitting method Proximal gradient method Q-linear rate of convergence 
An Inexact Proximal Method with Proximal Distances for Quasimonotone Equilibrium Problems
《Journal of the Operations Research Society of China》2017年第4期545-561,共17页Lennin Mallma Ramirez Erik Alex Papa Quiroz P.R.Oliveira 
the E.A.Papa Quiroz was supported by the Postdoctoral Scholarship CAPES-Fundação de AmparoàPesquisa do Estado do Rio de Janeiro(No.EditalPAPD-2011);P.R.Oliveira’s research was partially supported by Conselho Nacional de Desemvolvimento Científico e Tecnológico.
In this paper,we propose an inexact proximal point method to solve equilibrium problems using proximal distances and the diagonal subdifferential.Under some natural assumptions on the problem and the quasimonotonicit...
关键词：Equilibrium problems Quasimonotonicity Proximal distance Proximal method 
A Modified Proximal Gradient Method for a Family of Nonsmooth Convex Optimization Problems
《Journal of the Operations Research Society of China》2017年第3期391-403,共13页Ying-Yi Li Hai-Bin Zhang Fei Li 
the National Natural Science Foundation of China(No.61179033).
In this paper,we propose a modified proximal gradient method for solving a class of nonsmooth convex optimization problems,which arise in many contemporary statistical and signal processing applications.The proposed m...
关键词：Nonsmooth convex optimization Modified proximal gradient method Q-linear convergence 
An LQP-Based Two-Step Method for Structured Variational Inequalities被引量：1
《Journal of the Operations Research Society of China》2017年第3期301-317,共17页Hong-Jin He Kai Wang Xing-Ju Cai De-Ren Han 
the National Natural Science Foundation of China(Nos.11571087 and 71471051);the National Natural Science Foundation of Zhejiang Province(No.LY17A010028);The third author is supported by the National Natural Science Foundation of China(Nos.11431002 and 11401315);Jiangsu Provincial National Natural Science Foundation of China(No.BK20140914).
t The logarithmic quadratic proximal(LQP)regularization is a popular and powerful proximal regularization technique for solving monotone variational inequalities with nonnegative constraints.In this paper,we propose ...
关键词：Logarithmic quadratic proximal Projection method Variational inequality problem Traffic equilibrium problem 
First-Order Algorithms for Convex Optimization with Nonseparable Objective and Coupled Constraints被引量：7
《Journal of the Operations Research Society of China》2017年第2期131-159,共29页Xiang Gao Shu-Zhong Zhang 
National Science Foundation(No.CMMI-1462408)。
In this paper,we consider a block-structured convex optimization model,where in the objective the block variables are nonseparable and they are further linearly coupled in the constraint.For the 2-block case,we propos...
关键词：First-order algorithms ADMM Proximal gradient method Convex optimization Iteration complexity 
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