Xiang Li

According to our database, Xiang Li authored at least 18 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Fedpower: privacy-preserving distributed eigenspace estimation.

Xiao Guo, Xiang Li, Xiangyu Chang, Shusen Wang, Zhihua Zhang

Mach. Learn., December, 2024

A Random Projection Approach to Personalized Federated Learning: Enhancing Communication Efficiency, Robustness, and Fairness.

Yuze Han, Xiang Li, Shiyun Lin, Zhihua Zhang

J. Mach. Learn. Res., 2024

2023

Complete Asymptotic Analysis for Projected Stochastic Approximation and Debiased Variants.

Jiadong Liang, Yuze Han, Xiang Li, Zhihua Zhang

Proceedings of the 59th Annual Allerton Conference on Communication, 2023

A Statistical Analysis of Polyak-Ruppert Averaged Q-Learning.

Xiang Li, Wenhao Yang, Jiadong Liang, Zhihua Zhang, Michael I. Jordan

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Personalized Federated Learning towards Communication Efficiency, Robustness and Fairness.

Shiyun Lin, Yuze Han, Xiang Li, Zhihua Zhang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Asymptotic Behaviors of Projected Stochastic Approximation: A Jump Diffusion Perspective.

Jiadong Liang, Yuze Han, Xiang Li, Zhihua Zhang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Statistical Estimation and Online Inference via Local SGD.

Xiang Li, Jiadong Liang, Xiangyu Chang, Zhihua Zhang

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021

Polyak-Ruppert Averaged Q-Leaning is Statistically Efficient.

Xiang Li, Wenhao Yang, Zhihua Zhang, Michael I. Jordan

CoRR, 2021

Statistical Estimation and Inference via Local SGD in Federated Learning.

Xiang Li, Jiadong Liang, Xiangyu Chang, Zhihua Zhang

CoRR, 2021

Privacy-Preserving Distributed SVD via Federated Power.

Xiao Guo, Xiang Li, Xiangyu Chang, Shusen Wang, Zhihua Zhang

CoRR, 2021

Delayed Projection Techniques for Linearly Constrained Problems: Convergence Rates, Acceleration, and Applications.

Xiang Li, Zhihua Zhang

CoRR, 2021

Communication-Efficient Distributed SVD via Local Power Iterations.

Xiang Li, Shusen Wang, Kun Chen, Zhihua Zhang

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Finding the Near Optimal Policy via Adaptive Reduced Regularization in MDPs.

Wenhao Yang, Xiang Li, Guangzeng Xie, Zhihua Zhang

CoRR, 2020

On the Convergence of FedAvg on Non-IID Data.

Xiang Li, Kaixuan Huang, Wenhao Yang, Shusen Wang, Zhihua Zhang

Proceedings of the 8th International Conference on Learning Representations, 2020

Do Subsampled Newton Methods Work for High-Dimensional Data?

Xiang Li, Shusen Wang, Zhihua Zhang

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Communication Efficient Decentralized Training with Multiple Local Updates.

Xiang Li, Wenhao Yang, Shusen Wang, Zhihua Zhang

CoRR, 2019

A Unified Framework for Regularized Reinforcement Learning.

Xiang Li, Wenhao Yang, Zhihua Zhang

CoRR, 2019

A Regularized Approach to Sparse Optimal Policy in Reinforcement Learning.

Wenhao Yang, Xiang Li, Zhihua Zhang

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019