Zhihua Zhang

Most-cited papers

On the Convergence of FedAvg on Non-IID Data
Xiang Li, Kaixuan Huang, Wenhao Yang, Shusen Wang +1 more
2019International Conference on Learning Representations3,193 citations
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Federated Reinforcement Learning with Environment Heterogeneity
Hao Jin, Yang Peng, Wenhao Yang, Shusen Wang +1 more
2022International Conference on Artificial Intelligence and Statistics127 citations Open access
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Support Matrix Machines
Luo Luo, Yubo Xie, Zhihua Zhang, Wu-Jun Li
2015International Conference on Machine Learning105 citations
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Lipschitz Generative Adversarial Nets
Zhiming Zhou, Jia-Dong Liang, Yuxuan Song, Lan-Tao Yu +4 more
2019International Conference on Machine Learning86 citations
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Communication-Efficient Local Decentralized SGD Methods
Xiang Li, Wenhao Yang, Shusen Wang, Zhihua Zhang
201979 citations
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Wishart Mechanism for Differentially Private Principal Components Analysis
Wuxuan Jiang, Cong Xie, Zhihua Zhang
2015AAAI Conference on Artificial Intelligence67 citations Open access
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A Gram-Gauss-Newton Method Learning Overparameterized Deep Neural Networks for Regression Problems
Tianle Cai, Rui-Qi Gao, Jikai Hou, Siyu Chen +4 more
2019arXiv.org65 citations
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Toward theoretical understandings of robust Markov decision processes: Sample complexity and asymptotics
Wenhao Yang, Liangyu Zhang, Zhihua Zhang
2022Annals of Statistics60 citations Open access
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Communication Efficient Decentralized Training with Multiple Local Updates
Xiang Li, Wenhao Yang, Shusen Wang, Zhihua Zhang
2019arXiv.org57 citations
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Distillation ≈ Early Stopping? Harvesting Dark Knowledge Utilizing Anisotropic Information Retrieval For Overparameterized Neural Network
Bin Dong, Jikai Hou, Yiping Lu, Zhihua Zhang
2019arXiv.org45 citations
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Active Learning Approaches to Enhancing Neural Machine Translation: An Empirical Study
Yuekai Zhao, H. Zhang, Shuchang Zhou, Zhihua Zhang
2020Findings44 citations Open access
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A Regularized Approach to Sparse Optimal Policy in Reinforcement Learning
Wenhao Yang, Xiang Li, Zhihua Zhang
2019Neural Information Processing Systems43 citations
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Lower Complexity Bounds of Finite-Sum Optimization Problems: The Results and Construction
Yuze Han, Guangzeng Xie, Zhihua Zhang
2021Journal of machine learning research40 citations
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Towards More Efficient SPSD Matrix Approximation and CUR Matrix Decomposition
Shusen Wang, Zhihua Zhang, T. Zhang
2015Journal of machine learning research37 citations
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Communication-Efficient Distributed SVD via Local Power Iterations
Xiang Li, Shusen Wang, Kun Chen, Zhihua Zhang
2020International Conference on Machine Learning30 citations
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CPSG-MCMC: Clustering-Based Preprocessing method for Stochastic Gradient MCMC
Tianfan Fu, Zhihua Zhang
2017International Conference on Artificial Intelligence and Statistics29 citations
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Fast Fisher discriminant analysis with randomized algorithms
Haishan Ye, Yujun Li, Cheng Chen, Zhihua Zhang
2017Pattern Recognition29 citations
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Attention-via-Attention Neural Machine Translation
Shenjian Zhao, Zhihua Zhang
2018AAAI Conference on Artificial Intelligence26 citations Open access
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Approximate Newton Methods and Their Local Convergence
Haishan Ye, Luo Luo, Zhihua Zhang
2017International Conference on Machine Learning26 citations
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Robust Frequent Directions with Application in Online Learning
Luo Luo, Cheng Chen, Zhihua Zhang, Wu-Jun Li +1 more
2017Journal of machine learning research26 citations
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Lower Complexity Bounds for Finite-Sum Convex-Concave Minimax Optimization Problems
Guangzeng Xie, Luo Luo, Yi-Jiang Lian, Zhihua Zhang
2020International Conference on Machine Learning24 citations
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Online Statistical Inference for Nonlinear Stochastic Approximation with Markovian Data
Xiang Li, Jia-Dong Liang, Zhihua Zhang
202323 citations
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Near Optimal Stochastic Algorithms for Finite-Sum Unbalanced Convex-Concave Minimax Optimization
Luo Luo, Guangzeng Xie, Tong Zhang, Zhihua Zhang
2021arXiv.org23 citations
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Memory-Efficient Differentiable Transformer Architecture Search
Yuekai Zhao, Li Dong, Ye-Long Shen, Zhihua Zhang +2 more
2021Findings22 citations Open access
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Improved Analyses of the Randomized Power Method and Block Lanczos Method
Shusen Wang, Zhihua Zhang, Tong Zhang
2015arXiv.org22 citations
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Frequent Direction Algorithms for Approximate Matrix Multiplication with Applications in CCA
Qiaoming Ye, Luo Luo, Zhihua Zhang
2016International Joint Conference on Artificial Intelligence20 citations
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Towards explicit superlinear convergence rate for SR1
Haishan Ye, Dachao Lin, Xiangyu Chang, Zhihua Zhang
2022Mathematical programming19 citations
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Explicit Convergence Rates of Greedy and Random Quasi-Newton Methods
Dachao Lin, Haishan Ye, Zhihua Zhang
2021Journal of machine learning research17 citations
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Nesterov's Acceleration For Approximate Newton
Haishan Ye, Luo Luo, Zhihua Zhang
2017Journal of machine learning research17 citations
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Stochastic Distributed Optimization under Average Second-order Similarity: Algorithms and Analysis
Dachao Lin, Yuze Han, Haishan Ye, Zhihua Zhang
2023Neural Information Processing Systems16 citations Open access
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Greedy and Random Quasi-Newton Methods with Faster Explicit Superlinear Convergence
Dachao Lin, Haishan Ye, Zhihua Zhang
2021Neural Information Processing Systems16 citations
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Do Subsampled Newton Methods Work for High-Dimensional Data?
Xiang Li, Shusen Wang, Zhihua Zhang
2019AAAI Conference on Artificial Intelligence16 citations Open access
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A Stochastic Proximal Point Algorithm for Saddle-Point Problems
Luo Luo, Cheng Chen, Yujun Li, Guangzeng Xie +1 more
2019arXiv.org16 citations
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Approximate Newton Methods
Haishan Ye, Luo Luo, Zhihua Zhang
2017Journal of machine learning research16 citations
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Efficient Spectrum-Revealing CUR Matrix Decomposition
Cheng Chen, M. Gu, Zhihua Zhang, Wei-Nan Zhang +1 more
2020International Conference on Artificial Intelligence and Statistics14 citations
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DIPPA: An improved Method for Bilinear Saddle Point Problems
Guangzeng Xie, Yuze Han, Zhihua Zhang
2021arXiv.org12 citations
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Quasi-Newton Hamiltonian Monte Carlo
Tianfan Fu, Luo Luo, Zhihua Zhang
2016Conference on Uncertainty in Artificial Intelligence12 citations
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On the Global Convergence of Majorization Minimization Algorithms for Nonconvex Optimization Problems
Yangyang Kang, Zhihua Zhang, Wu-Jun Li
2015arXiv.org10 citations
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Explicit Superlinear Convergence Rates of The SR1 Algorithm
Haishan Ye, Dachao Lin, Zhihua Zhang, Xiangyu Chang
20219 citations
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Train Once, and Decode As You Like
Chao Tian, Yifei Wang, Hao Cheng, Yi-Jiang Lian +1 more
2020International Conference on Computational Linguistics9 citations Open access
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Explicit Superlinear Convergence Rates of Broyden's Methods in Nonlinear Equations
Dachao Lin, Haishan Ye, Zhihua Zhang
20218 citations
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An Asymptotically Optimal Multi-Armed Bandit Algorithm and Hyperparameter Optimization
Yimin Huang, Yujun Li, Zhen-Guo Li, Zhihua Zhang
2020arXiv.org8 citations
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An Efficient Character-Level Neural Machine Translation
Shenjian Zhao, Zhihua Zhang
2016arXiv.org8 citations
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S-PowerGraph: Streaming Graph Partitioning for Natural Graphs by Vertex-Cut
Cong Xie, Wu-Jun Li, Zhihua Zhang
2015arXiv.org8 citations
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Privacy-Preserving Distributed SVD via Federated Power
Xiao Guo, Xiang Li, Xiangyu Chang, Shusen Wang +1 more
2021arXiv.org7 citations
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Polyak-Ruppert Averaged Q-Leaning is Statistically Efficient
Xiang Li, Wenhao Yang, Zhihua Zhang, Michael I. Jordan
2021arXiv.org7 citations
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Towards More Efficient Symmetric Matrix Sketching and the CUR Matrix Decomposition
Shusen Wang, Zhihua Zhang, Tong Zhang
20157 citations
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Faster Directional Convergence of Linear Neural Networks under Spherically Symmetric Data
Dachao Lin, Ruoyu Sun, Zhihua Zhang
2021Neural Information Processing Systems6 citations
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Greedy and Random Broyden's Methods with Explicit Superlinear Convergence Rates in Nonlinear Equations
Haishan Ye, Dachao Lin, Zhihua Zhang
2021arXiv.org6 citations
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Statistical Estimation and Inference via Local SGD in Federated Learning
Xiang Li, Jia-Dong Liang, Xiangyu Chang, Zhihua Zhang
2021arXiv.org6 citations
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