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h5 指数:31
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#10 Mathematical Optimization

标题/作者	引用次数	年份
Momentum and stochastic momentum for stochastic gradient, Newton, proximal point and subspace descent methods N Loizou, P Richtárik Computational Optimization and Applications 77 (3), 653-710	137	2020
Modified hybrid projection methods for finding common solutions to variational inequality problems D Van Hieu, PK Anh, LD Muu Computational Optimization and Applications 66 (1), 75-96	137	2017
Formulating an n-person noncooperative game as a tensor complementarity problem ZH Huang, L Qi Computational Optimization and Applications 66 (3), 557-576	103	2017
Structured nonconvex and nonsmooth optimization: algorithms and iteration complexity analysis B Jiang, T Lin, S Ma, S Zhang Computational Optimization and Applications 72 (1), 115-157	102	2019
Forward–backward quasi-Newton methods for nonsmooth optimization problems L Stella, A Themelis, P Patrinos Computational Optimization and Applications 67 (3), 443-487	101	2017
A proximal difference-of-convex algorithm with extrapolation B Wen, X Chen, TK Pong Computational Optimization and Applications 69 (2), 297-324	99	2018
Mitigating the curse of dimensionality: sparse grid characteristics method for optimal feedback control and HJB equations W Kang, LC Wilcox Computational Optimization and Applications 68 (2), 289-315	77	2017
On the convergence of the direct extension of ADMM for three-block separable convex minimization models with one strongly convex function X Cai, D Han, X Yuan Computational Optimization and Applications 66 (1), 39-73	71	2017
Asymmetric forward–backward–adjoint splitting for solving monotone inclusions involving three operators P Latafat, P Patrinos Computational Optimization and Applications 68 (1), 57-93	60	2017
A Riemannian conjugate gradient method for optimization on the Stiefel manifold X Zhu Computational Optimization and Applications 67 (1), 73-110	60	2017
Smoothing algorithms for computing the projection onto a Minkowski sum of convex sets X Qin, NT An Computational Optimization and Applications 74 (3), 821-850	59	2019
A note on the convergence of ADMM for linearly constrained convex optimization problems L Chen, D Sun, KC Toh Computational Optimization and Applications 66 (2), 327-343	54	2017
A two-stage stochastic programming approach for influence maximization in social networks HH Wu, S Küçükyavuz Computational Optimization and Applications 69 (3), 563-595	52	2018
MIP-based instantaneous control of mixed-integer PDE-constrained gas transport problems M Gugat, G Leugering, A Martin, M Schmidt, M Sirvent, D Wintergerst Computational Optimization and Applications 70 (1), 267-294	52	2018
Approximate ADMM algorithms derived from Lagrangian splitting J Eckstein, W Yao Computational Optimization and Applications 68 (2), 363-405	52	2017
Accelerated Bregman proximal gradient methods for relatively smooth convex optimization F Hanzely, P Richtárik, L Xiao Computational Optimization and Applications 79 (2), 405-440	50	2021
A copositive approach for two-stage adjustable robust optimization with uncertain right-hand sides G Xu, S Burer Computational Optimization and Applications 70 (1), 33-59	49	2018
Generalized symmetric ADMM for separable convex optimization J Bai, J Li, F Xu, H Zhang Computational Optimization and Applications 70 (1), 129-170	47	2018
Convergence of a Scholtes-type regularization method for cardinality-constrained optimization problems with an application in sparse robust portfolio optimization M Branda, M Bucher, M Červinka, A Schwartz Computational Optimization and Applications 70 (2), 503-530	43	2018
Mesh-based Nelder–Mead algorithm for inequality constrained optimization C Audet, C Tribes Computational Optimization and Applications 71 (2), 331-352	39	2018

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