Xiang Li - RankMe

21 papers A* 7A 1Journal 12Unranked 1

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	A Random Projection Approach to Personalized Federated Learning: Enhancing Communication Efficiency, Robustness, and Fairness. J. Mach. Learn. Res. Yuze Han, Xiang Li, Shiyun Lin, Zhihua Zhang
2024	J	`jnl`	Fedpower: privacy-preserving distributed eigenspace estimation. Mach. Learn. Xiao Guo, Xiang Li, Xiangyu Chang, Shusen Wang, Zhihua Zhang
2023	A	`conf`	A Statistical Analysis of Polyak-Ruppert Averaged Q-Learning. AISTATS Xiang Li, Wenhao Yang, Jiadong Liang, Zhihua Zhang, Michael I. Jordan
2023	—	`conf`	Complete Asymptotic Analysis for Projected Stochastic Approximation and Debiased Variants. Allerton Jiadong Liang, Yuze Han, Xiang Li, Zhihua Zhang
2022	A*	`conf`	Asymptotic Behaviors of Projected Stochastic Approximation: A Jump Diffusion Perspective. NeurIPS Jiadong Liang, Yuze Han, Xiang Li, Zhihua Zhang
2022	A*	`conf`	Personalized Federated Learning towards Communication Efficiency, Robustness and Fairness. NeurIPS Shiyun Lin, Yuze Han, Xiang Li, Zhihua Zhang
2022	A*	`conf`	Statistical Estimation and Online Inference via Local SGD. COLT Xiang Li, Jiadong Liang, Xiangyu Chang, Zhihua Zhang
2021	A*	`conf`	Communication-Efficient Distributed SVD via Local Power Iterations. ICML Xiang Li, Shusen Wang, Kun Chen, Zhihua Zhang
2021	J	`jnl`	Delayed Projection Techniques for Linearly Constrained Problems: Convergence Rates, Acceleration, and Applications. CoRR Xiang Li, Zhihua Zhang
2021	J	`jnl`	Polyak-Ruppert Averaged Q-Leaning is Statistically Efficient. CoRR Xiang Li, Wenhao Yang, Zhihua Zhang, Michael I. Jordan
2021	J	`jnl`	Privacy-Preserving Distributed SVD via Federated Power. CoRR Xiao Guo, Xiang Li, Xiangyu Chang, Shusen Wang, Zhihua Zhang
2021	J	`jnl`	Statistical Estimation and Inference via Local SGD in Federated Learning. CoRR Xiang Li, Jiadong Liang, Xiangyu Chang, Zhihua Zhang
2020	J	`jnl`	Communication-Efficient Distributed SVD via Local Power Iterations. CoRR Xiang Li, Shusen Wang, Kun Chen, Zhihua Zhang
2020	A*	`conf`	Do Subsampled Newton Methods Work for High-Dimensional Data? AAAI Xiang Li, Shusen Wang, Zhihua Zhang
2020	J	`jnl`	Finding the Near Optimal Policy via Adaptive Reduced Regularization in MDPs. CoRR Wenhao Yang, Xiang Li, Guangzeng Xie, Zhihua Zhang
2020	A*	`conf`	On the Convergence of FedAvg on Non-IID Data. ICLR Xiang Li, Kaixuan Huang, Wenhao Yang, Shusen Wang, Zhihua Zhang
2019	A*	`conf`	A Regularized Approach to Sparse Optimal Policy in Reinforcement Learning. NeurIPS Wenhao Yang, Xiang Li, Zhihua Zhang
2019	J	`jnl`	A Unified Framework for Regularized Reinforcement Learning. CoRR Xiang Li, Wenhao Yang, Zhihua Zhang
2019	J	`jnl`	Communication Efficient Decentralized Training with Multiple Local Updates. CoRR Xiang Li, Wenhao Yang, Shusen Wang, Zhihua Zhang
2019	J	`jnl`	Do Subsampled Newton Methods Work for High-Dimensional Data? CoRR Xiang Li, Shusen Wang, Zhihua Zhang
2019	J	`jnl`	On the Convergence of FedAvg on Non-IID Data. CoRR Xiang Li, Kaixuan Huang, Wenhao Yang, Shusen Wang, Zhihua Zhang