Luo, Luo

37 publications

NeurIPS 2025 A Near-Optimal Algorithm for Decentralized Convex-Concave Finite-Sum Minimax Optimization Hongxu Chen, Ke Wei, Haishan Ye, Luo Luo

ICML 2025 A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization Kunjie Ren, Luo Luo

NeurIPS 2025 Accelerated Evolving Set Processes for Local PageRank Computation BinbinHuang, Luo Luo, Yanghua Xiao, Deqing Yang, Baojian Zhou

AAAI 2025 An Enhanced Levenberg-Marquardt Method via Gram Reduction Chengchang Liu, Luo Luo, John C. S. Lui

COLT 2025 Solving Convex-Concave Problems with $\mathcal{O}(\epsilon^{-4/7})$ Second-Order Oracle Complexity Lesi Chen, Chengchang Liu, Luo Luo, Jingzhao Zhang

AISTATS 2024 An Efficient Stochastic Algorithm for Decentralized Nonconvex-Strongly-Concave Minimax Optimization Lesi Chen, Haishan Ye, Luo Luo

ICML 2024 Decentralized Convex Finite-Sum Optimization with Better Dependence on Condition Numbers Yuxing Liu, Lesi Chen, Luo Luo

AAAI 2024 Decentralized Gradient-Free Methods for Stochastic Non-Smooth Non-Convex Optimization Zhenwei Lin, Jingfan Xia, Qi Deng, Luo Luo

NeurIPS 2024 Gradient-Free Methods for Nonconvex Nonsmooth Stochastic Compositional Optimization Zhuanghua Liu, Luo Luo, Bryan Kian Hsiang Low

AAAI 2024 Incremental Quasi-Newton Methods with Faster Superlinear Convergence Rates Zhuanghua Liu, Luo Luo, Bryan Kian Hsiang Low

JMLR 2024 Near-Optimal Algorithms for Making the Gradient Small in Stochastic Minimax Optimization Lesi Chen, Luo Luo

NeurIPS 2024 Near-Optimal Distributed Minimax Optimization Under the Second-Order Similarity Qihao Zhou, Haishan Ye, Luo Luo

ICML 2024 On the Complexity of Finite-Sum Smooth Optimization Under the Polyak–Łojasiewicz Condition Yunyan Bai, Yuxing Liu, Luo Luo

NeurIPS 2024 Optimizing over Multiple Distributions Under Generalized Quasar-Convexity Condition Shihong Ding, Long Yang, Luo Luo, Cong Fang

ICML 2024 Zeroth-Order Methods for Constrained Nonconvex Nonsmooth Stochastic Optimization Zhuanghua Liu, Cheng Chen, Luo Luo, Bryan Kian Hsiang Low

NeurIPSW 2023 Accelerating Inexact HyperGradient Descent for Bilevel Optimization Haikuo Yang, Luo Luo, Chris Junchi Li, Michael Jordan, Maryam Fazel

NeurIPS 2023 Block Broyden's Methods for Solving Nonlinear Equations Chengchang Liu, Cheng Chen, Luo Luo, John C.S. Lui

ICML 2023 Faster Gradient-Free Algorithms for Nonsmooth Nonconvex Stochastic Optimization Lesi Chen, Jing Xu, Luo Luo

JMLR 2023 Multi-Consensus Decentralized Accelerated Gradient Descent Haishan Ye, Luo Luo, Ziang Zhou, Tong Zhang

NeurIPS 2022 Faster Stochastic Algorithms for Minimax Optimization Under Polyak-{\L}ojasiewicz Condition Lesi Chen, Boyuan Yao, Luo Luo

NeurIPS 2022 Finding Second-Order Stationary Points in Nonconvex-Strongly-Concave Minimax Optimization Luo Luo, Yujun Li, Cheng Chen

NeurIPS 2022 Quasi-Newton Methods for Saddle Point Problems Chengchang Liu, Luo Luo

JMLR 2021 Approximate Newton Methods Haishan Ye, Luo Luo, Zhihua Zhang

AAAI 2021 Revisiting Co-Occurring Directions: Sharper Analysis and Efficient Algorithm for Sparse Matrices Luo Luo, Cheng Chen, Guangzeng Xie, Haishan Ye

NeurIPS 2020 Decentralized Accelerated Proximal Gradient Descent Haishan Ye, Ziang Zhou, Luo Luo, Tong Zhang

NeurIPS 2020 Efficient Projection-Free Algorithms for Saddle Point Problems Cheng Chen, Luo Luo, Weinan Zhang, Yong Yu

IJCAI 2020 Efficient and Robust High-Dimensional Linear Contextual Bandits Cheng Chen, Luo Luo, Weinan Zhang, Yong Yu, Yijiang Lian

ICML 2020 Lower Complexity Bounds for Finite-Sum Convex-Concave Minimax Optimization Problems Guangzeng Xie, Luo Luo, Yijiang Lian, Zhihua Zhang

JMLR 2020 Nesterov's Acceleration for Approximate Newton Haishan Ye, Luo Luo, Zhihua Zhang

NeurIPS 2020 Stochastic Recursive Gradient Descent Ascent for Stochastic Nonconvex-Strongly-Concave Minimax Problems Luo Luo, Haishan Ye, Zhichao Huang, Tong Zhang

JMLR 2019 Robust Frequent Directions with Application in Online Learning Luo Luo, Cheng Chen, Zhihua Zhang, Wu-Jun Li, Tong Zhang

ICML 2017 Approximate Newton Methods and Their Local Convergence Haishan Ye, Luo Luo, Zhihua Zhang

AAAI 2017 Communication Lower Bounds for Distributed Convex Optimization: Partition Data on Features Zihao Chen, Luo Luo, Zhihua Zhang

IJCAI 2016 Frequent Direction Algorithms for Approximate Matrix Multiplication with Applications in CCA Qiaomin Ye, Luo Luo, Zhihua Zhang

UAI 2016 Quasi-Newton Hamiltonian Monte Carlo Tianfan Fu, Luo Luo, Zhihua Zhang

JMLR 2016 SPSD Matrix Approximation Vis Column Selection: Theories, Algorithms, and Extensions Shusen Wang, Luo Luo, Zhihua Zhang

ICML 2015 Support Matrix Machines Luo Luo, Yubo Xie, Zhihua Zhang, Wu-Jun Li