Zhaoxian Wu

According to our database, Zhaoxian Wu authored at least 17 papers between 2020 and 2025.

Collaborative distances:

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

2025

Analog In-memory Training on General Non-ideal Resistive Elements: The Impact of Response Functions.

Zhaoxian Wu, Quan Xiao, Tayfun Gokmen, Omobayode Fagbohungbe, Tianyi Chen

CoRR, February, 2025

Single-Timescale Multi-Sequence Stochastic Approximation Without Fixed Point Smoothness: Theories and Applications.

Yue Huang, Zhaoxian Wu, Shiqian Ma, Qing Ling

IEEE Trans. Signal Process., 2025

2024

Byzantine-Robust Distributed Online Learning: Taming Adversarial Participants in An Adversarial Environment.

Xingrong Dong, Zhaoxian Wu, Qing Ling, Zhi Tian

IEEE Trans. Signal Process., 2024

Pipeline Gradient-based Model Training on Analog In-memory Accelerators.

Zhaoxian Wu, Quan Xiao, Tayfun Gokmen, Hsinyu Tsai, Kaoutar El Maghraoui, Tianyi Chen

CoRR, 2024

On the Trade-off between Flatness and Optimization in Distributed Learning.

Ying Cao, Zhaoxian Wu, Kun Yuan, Ali H. Sayed

CoRR, 2024

Towards Exact Gradient-based Training on Analog In-memory Computing.

Zhaoxian Wu, Tayfun Gokmen, Malte J. Rasch, Tianyi Chen

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

On the Convergence of Single-Timescale Multi-Sequence Stochastic Approximation Without Fixed Point Smoothness.

Yue Huang, Zhaoxian Wu, Qing Ling

Proceedings of the IEEE International Conference on Acoustics, 2024

2023

Byzantine-Resilient Decentralized Stochastic Optimization With Robust Aggregation Rules.

Zhaoxian Wu, Tianyi Chen, Qing Ling

IEEE Trans. Signal Process., 2023

Distributed Online Learning With Adversarial Participants In An Adversarial Environment.

Xingrong Dong, Zhaoxian Wu, Qing Ling, Zhi Tian

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

Communication-Censored Distributed Stochastic Gradient Descent.

Weiyu Li, Zhaoxian Wu, Tianyi Chen, Liping Li, Qing Ling

IEEE Trans. Neural Networks Learn. Syst., 2022

Byzantine-robust variance-reduced federated learning over distributed non-i.i.d. data.

Jie Peng, Zhaoxian Wu, Qing Ling, Tianyi Chen

Inf. Sci., 2022

A Byzantine-Resilient Dual Subgradient Method for Vertical Federated Learning.

Kun Yuan, Zhaoxian Wu, Qing Ling

Proceedings of the IEEE International Conference on Acoustics, 2022

2021

Byzantine-Resilient Decentralized Policy Evaluation With Linear Function Approximation.

Zhaoxian Wu, Han Shen, Tianyi Chen, Qing Ling

IEEE Trans. Signal Process., 2021

Byzantine-Resilient Decentralized TD Learning with Linear Function Approximation.

Zhaoxian Wu, Han Shen, Tianyi Chen, Qing Ling

Proceedings of the IEEE International Conference on Acoustics, 2021

2020

Federated Variance-Reduced Stochastic Gradient Descent With Robustness to Byzantine Attacks.

Zhaoxian Wu, Qing Ling, Tianyi Chen, Georgios B. Giannakis

IEEE Trans. Signal Process., 2020

Byzantine-Robust Variance-Reduced Federated Learning over Distributed Non-i.i.d. Data.

Jie Peng, Zhaoxian Wu, Qing Ling

CoRR, 2020

Resilient to Byzantine Attacks Finite-Sum Optimization Over Networks.

Zhaoxian Wu, Qing Ling, Tianyi Chen, Georgios B. Giannakis

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020