Publications
- Under Review
- Zhang, X., Hong. M, & Chen, J. GLASU: A Communication-Efficient Algorithm for Federated Learning with Vertically Distributed Graph Data, Submitted to International Conference on Machine Learning, 2023.
- 2023
- Zhang, X., Hong, M., & Elia, N. A Unified Framework to Understand Decentralized and Federated Optimization Algorithms: A Multi-Rate Feedback Control Perspective, SIAM Journal on Optimization, (NeurIPS-2021 Workshop on New Frontiers in Federated Learning. (Accepted as Contributed Talk))
- 2022
- Zhang, X., Hong, M., Dhople S., & Elia, N. A Stochastic Multi-Rate Control Framework For Modeling Distributed Optimization Algorithms, International Conference on Machine Learning, 2022. (Accept for Spotlight Presentation) https://proceedings.mlr.press/v162/zhang22j.html
- Zhang, X., Chen, X., Hong, M., Wu, Z.S. & Yi, J. Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy, International Conference on Machine Learning, 2022. (Accept for Spotlight Presentation) https://proceedings.mlr.press/v162/zhang22b.html
- Liu Y., Zhang X., Kang Y., Li L., & Hong M. FedBCD: A Communication-Efficient Collaborative Learning Framework for Distributed Features, IEEE Transactions on Signal Processing, 2022, IEEE. https://ieeexplore.ieee.org/document/9855231 (Co-first author and corresponding author).
- 2021
- Zhang, X., Hong, M., Dhople, S., Yin, W., & Liu, Y. FedPD: A Federated Learning Framework with Adaptivity to Non-IID Data. IEEE Transactions on Signal Processing, 2022, IEEE. https://ieeexplore.ieee.org/document/9556559
- 2020
- Chang, T. H., Hong, M., Wai, H. T., Zhang, X., & Lu, S. Distributed learning in the nonconvex world: From batch data to streaming and beyond. IEEE Signal Processing Magazine, 37(3), 26-38.
- Zhang, X., Yin, W., Hong, M. & Chen, T. Hybrid FL: Algorithms and Implementation, Conference on Neural Information Processing Systems 2020 Workshop on Scalability, Privacy, and Security in Federated Learning. (Best Student Paper Award)
- Zhang, X., Purba, V., Hong, M., & Dhople, S. A sum-of-squares optimization method for learning and controlling photovoltaic systems. In 2020 American Control Conference (ACC) (pp. 2376-2381). IEEE.
- 2019
- Zhang, X., Sartori, J., Hong, M., & Dhople, S. Implementing First-order Optimization Methods: Algorithmic Considerations and Bespoke Microcontrollers. In 2019 53rd Asilomar Conference on Signals, Systems, and Computers (pp. 296-300). IEEE.
- Lu, S., Zhang, X., Sun, H., & Hong, M. GNSD: A gradient-tracking based nonconvex stochastic algorithm for decentralized optimization. In 2019 IEEE Data Science Workshop (DSW) (pp. 315-321). IEEE.
- 2018
- Zhang, X., Du, Y., Chen, F., Qin, L., & Ling, Q. Indoor Position Control of a Quadrotor UAV with Monocular Vision Feedback. In 2018 37th Chinese Control Conference (CCC) (pp. 9760-9765). IEEE.
- Du, Y., Zhang, X., Qin, L., Wu, G., & Ling, Q. State estimation of autonomous rotorcraft MAVs under indoor environments. In 2018 Chinese Control And Decision Conference (CCDC) (pp. 4420-4424). IEEE.
You can also find my articles on my Google Scholar profile