Luo Luo

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Zhihua ZhangProfessor of Computer Science, Shanghai Jiao Tong UniversityVerifierad e-postadress på zju.edu.cn
Haishan Ye西安交通大学Verifierad e-postadress på xjtu.edu.cn
Tong ZhangUIUCVerifierad e-postadress på tongzhang-ml.org
Cheng ChenEast China Normal UniversityVerifierad e-postadress på sei.ecnu.edu.cn
Chengchang LiuThe Chinese University of Hong KongVerifierad e-postadress på mail.ustc.edu.cn
Lesi ChenPhD student, IIIS, Tsinghua UniversityVerifierad e-postadress på fudan.edu.cn
Wu-Jun LiNanjing UniversityVerifierad e-postadress på nju.edu.cn
Ziang ZhouPhD Student at The Hong Kong Polytechnic UniversityVerifierad e-postadress på connect.polyu.hk
Yubo XieÉcole polytechnique fédérale de LausanneVerifierad e-postadress på epfl.ch
Zhichao HuangHong Kong University of Science and TechnologyVerifierad e-postadress på connect.ust.hk
Shusen WangMetaVerifierad e-postadress på meta.com
Weinan ZhangProfessor, Shanghai Jiao Tong UniversityVerifierad e-postadress på sjtu.edu.cn
Yong Yu (俞勇)Professor, Shanghai Jiao Tong UniversityVerifierad e-postadress på sjtu.edu.cn
Zhuanghua LiuNational University of SingaporeVerifierad e-postadress på u.nus.edu
Qiaomin YeShanghai Jiao Tong UniversityVerifierad e-postadress på sjtu.edu.cn
Bryan Kian Hsiang LowAssociate Professor (with tenure), Department of Computer Science, National University of SingaporeVerifierad e-postadress på comp.nus.edu.sg
Tianfan FuNanjing UniversityVerifierad e-postadress på nju.edu.cn
Boyuan YaoUniversity of Texas at AustinVerifierad e-postadress på utexas.edu
Chris J LiUniversity of California, BerkeleyVerifierad e-postadress på berkeley.edu
Jing XuTsinghua UniversityVerifierad e-postadress på mails.tsinghua.edu.cn

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Luo Luo

Fudan University

Verifierad e-postadress på fudan.edu.cn - Startsida

Machine Learning Optimization Linear Algebra.


Titel Sortera efter citat Sortera efter år Sortera efter titel	Citeras av Citeras av	År
Support matrix machines L Luo, Y Xie, Z Zhang, WJ Li International Conference on Machine Learning (ICML), 2015	139	2015
Stochastic Recursive Gradient Descent Ascent for Stochastic Nonconvex-Strongly-Concave Minimax Problems L Luo, H Ye, Z Huang, T Zhang Advances in Neural Information Processing Systems (NeurIPS), 2020	134	2020
Multi-Consensus Decentralized Accelerated Gradient Descent H Ye, L Luo, Z Zhou, T Zhang Journal of Machine Learning Research (JMLR) 24 (306), 1-50, 2023	67	2023
SPSD matrix approximation vis column selection: theories, algorithms, and extensions S Wang, L Luo, Z Zhang Journal of Machine Learning Research (JMLR) 17 (1), 1697-1745, 2016	53*	2016
Decentralized Accelerated Proximal Gradient Descent H Ye, Z Zhou, L Luo, T Zhang Advances in Neural Information Processing Systems (NeurIPS), 2020	36	2020
Finding second-order stationary points in nonconvex-strongly-concave minimax optimization. L Luo, Y Li, C Chen Advances in Neural Information Processing Systems (NeurIPS), 2022	32	2022
Robust frequent directions with application in online learning L Luo, C Chen, Z Zhang, WJ Li, T Zhang Journal of Machine Learning Research (JMLR) 20 (45), 1-41, 2019	27	2019
Approximate Newton methods and their local convergence H Ye, L Luo, Z Zhang International Conference on Machine Learning (ICML), 2017	26	2017
Approximate Newton Methods H Ye, L Luo, Z Zhang Journal of Machine Learning Research (JMLR) 22 (66), 1-41, 2021	24*	2021
Lower Complexity Bounds for Finite-Sum Convex-Concave Minimax Optimization Problems G Xie, L Luo, Y Lian, Z Zhang International Conference on Machine Learning (ICML), 2020	23	2020
Quasi-Newton Methods for Saddle Point Problems C Liu, L Luo Advances in Neural Information Processing Systems (NeurIPS), 2022	22*	2022
Frequent direction algorithms for approximate matrix multiplication with applications in CCA Q Ye, L Luo, Z Zhang International Joint Conference on Artificial Intelligence (IJCAI), 2016	22	2016
Near Optimal Stochastic Algorithms for Finite-Sum Unbalanced Convex-Concave Minimax Optimization L Luo, G Xie, T Zhang, Z Zhang arXiv preprint arXiv:2106.01761, 2021	21	2021
Nesterov's Acceleration for Approximate Newton H Ye, L Luo, Z Zhang Journal of Machine Learning Research (JMLR) 21 (142), 1-37, 2020	18	2020
Quasi-Newton Hamiltonian Monte Carlo. T Fu, L Luo, Z Zhang Conference on Uncertainty in Artificial Intelligence (UAI), 2016	18	2016
Faster Stochastic Algorithms for Minimax Optimization under Polyak-Łojasiewicz Condition L Chen, B Yao, L Luo Advances in Neural Information Processing Systems (NeurIPS), 2022	15	2022
Accelerating inexact hypergradient descent for bilevel optimization H Yang, L Luo, CJ Li, M Jordan, M Fazel OPT 2023: Optimization for Machine Learning, 2023	14	2023
Faster Gradient-Free Algorithms for Nonsmooth Nonconvex Stochastic Optimization L Chen, J Xu, L Luo International Conference on Machine Learning (ICML), 2023	14	2023
A Stochastic Proximal Point Algorithm for Saddle-Point Problems L Luo, C Chen, Y Li, G Xie, Z Zhang arXiv preprint arXiv:1909.06946, 2019	13	2019
Efficient Projection-Free Algorithms for Saddle Point Problems C Chen, L Luo, W Zhang, Y Yu Advances in Neural Information Processing Systems (NeurIPS), 2020	12	2020

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