Resilient to Byzantine Attacks Finite-Sum Optimization Over Networks. - Zhaoxian Wu; Qing Ling 001; Tianyi Chen; Georgios B. Giannakis (ICASSP, 2020)

Byzantine-Robust Variance-Reduced Federated Learning over Distributed Non-i.i.d. Data. - Jie Peng; Zhaoxian Wu; Qing Ling 001 (CoRR, 2020)

Federated Variance-Reduced Stochastic Gradient Descent With Robustness to Byzantine Attacks. - Zhaoxian Wu; Qing Ling 001; Tianyi Chen; Georgios B. Giannakis (IEEE Trans. Signal Process., 2020)

Byzantine-Resilient Decentralized TD Learning with Linear Function Approximation. - Zhaoxian Wu; Han Shen; Tianyi Chen; Qing Ling 001 (ICASSP, 2021)

Byzantine-Resilient Decentralized Policy Evaluation With Linear Function Approximation. - Zhaoxian Wu; Han Shen; Tianyi Chen; Qing Ling 001 (IEEE Trans. Signal Process., 2021)

A Byzantine-Resilient Dual Subgradient Method for Vertical Federated Learning. - Kun Yuan 001; Zhaoxian Wu; Qing Ling 001 (ICASSP, 2022)

Byzantine-robust variance-reduced federated learning over distributed non-i.i.d. data. - Jie Peng; Zhaoxian Wu; Qing Ling 001; Tianyi Chen (Inf. Sci., 2022)

Communication-Censored Distributed Stochastic Gradient Descent. - Weiyu Li; Zhaoxian Wu; Tianyi Chen; Liping Li 004; Qing Ling 001 (IEEE Trans. Neural Networks Learn. Syst., 2022)

Distributed Online Learning With Adversarial Participants In An Adversarial Environment. - Xingrong Dong; Zhaoxian Wu; Qing Ling 001; Zhi Tian (ICASSP, 2023)

Byzantine-Resilient Decentralized Stochastic Optimization With Robust Aggregation Rules. - Zhaoxian Wu; Tianyi Chen; Qing Ling 001 (IEEE Trans. Signal Process., 2023)

On the Convergence of Single-Timescale Multi-Sequence Stochastic Approximation Without Fixed Point Smoothness. - Yue Huang; Zhaoxian Wu; Qing Ling 001 (ICASSP, 2024)

Towards Exact Gradient-based Training on Analog In-memory Computing. - Zhaoxian Wu; Tayfun Gokmen; Malte J. Rasch; Tianyi Chen (NeurIPS, 2024)

On the Trade-off between Flatness and Optimization in Distributed Learning. - Ying Cao; Zhaoxian Wu; Kun Yuan 001; Ali H. Sayed (CoRR, 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)

Byzantine-Robust Distributed Online Learning: Taming Adversarial Participants in An Adversarial Environment. - Xingrong Dong; Zhaoxian Wu; Qing Ling 001; Zhi Tian (IEEE Trans. Signal Process., 2024)

Single-Timescale Multi-Sequence Stochastic Approximation Without Fixed Point Smoothness: Theories and Applications. - Yue Huang; Zhaoxian Wu; Shiqian Ma; Qing Ling 001 (IEEE Trans. Signal Process., 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, 2025)