Anarchic federated learning H Yang, X Zhang, P Khanduri, J Liu
International Conference on Machine Learning, 25331-25363, 2022
81 2022 Byzantine-resilient stochastic gradient descent for distributed learning: A lipschitz-inspired coordinate-wise median approach H Yang, X Zhang, M Fang, J Liu
2019 IEEE 58th Conference on Decision and Control (CDC), 5832-5837, 2019
55 2019 Compressed distributed gradient descent: Communication-efficient consensus over networks X Zhang, J Liu, Z Zhu, ES Bentley
IEEE INFOCOM 2019-IEEE Conference on Computer Communications, 2431-2439, 2019
38 2019 Drug–target interaction prediction by integrating multiview network data X Zhang, L Li, MK Ng, S Zhang
Computational biology and chemistry 69, 185-193, 2017
37 2017 Private and communication-efficient edge learning: A sparse differential Gaussian-masking distributed SGD approach X Zhang, M Fang, J Liu, Z Zhu
Proceedings of the Twenty-First International Symposium on Theory …, 2020
33 2020 Taming communication and sample complexities in decentralized policy evaluation for cooperative multi-agent reinforcement learning X Zhang, Z Liu, J Liu, Z Zhu, S Lu
Advances in Neural Information Processing Systems 34, 18825-18838, 2021
31 2021 Learning coefficient heterogeneity over networks: a distributed spanning-tree-based fused-lasso regression X Zhang, J Liu, Z Zhu
Journal of the American Statistical Association 119 (545), 485-497, 2024
25 * 2024 Taming convergence for asynchronous stochastic gradient descent with unbounded delay in non-convex learning X Zhang, J Liu, Z Zhu
2020 59th IEEE Conference on Decision and Control (CDC), 3580-3585, 2020
25 2020 NET-FLEET: Achieving linear convergence speedup for fully decentralized federated learning with heterogeneous data X Zhang, M Fang, Z Liu, H Yang, J Liu, Z Zhu
Proceedings of the Twenty-Third International Symposium on Theory …, 2022
16 2022 SAGDA: Achieving H Yang, Z Liu, X Zhang, J Liu
Advances in Neural Information Processing Systems 35, 7142-7154, 2022
14 2022 Interact: Achieving low sample and communication complexities in decentralized bilevel learning over networks Z Liu, X Zhang, P Khanduri, S Lu, J Liu
Proceedings of the Twenty-Third International Symposium on Theory …, 2022
14 2022 GT-STORM: Taming sample, communication, and memory complexities in decentralized non-convex learning X Zhang, J Liu, Z Zhu, ES Bentley
Proceedings of the Twenty-second International Symposium on Theory …, 2021
13 2021 Electricity consumer archetypes study based on functional data analysis and K-means algorithm Z Xin, G Weiguo, SU Yun
Power System Technology 39 (2), 3153-3162, 2015
11 * 2015 PRECISION: Decentralized Constrained Min-Max Learning with Low Communication and Sample Complexities Z Liu, X Zhang, S Lu, J Liu
Mobihoc 2023, 2023
10 2023 Fast and robust sparsity learning over networks: A decentralized surrogate median regression approach W Liu, X Mao, X Zhang
IEEE Transactions on Signal Processing 70, 797-809, 2022
10 2022 ELSA: Efficient Label Shift Adaptation through the Lens of Semiparametric Models Q Tian, X Zhang, J Zhao
Proc. ICML 2023, 2023
9 2023 Low sample and communication complexities in decentralized learning: A triple hybrid approach X Zhang, J Liu, Z Zhu, ES Bentley
IEEE INFOCOm 2021-IEEE conference on computer communications, 1-10, 2021
7 2021 Clustered coefficient regression models for poisson process with an application to seasonal warranty claim data X Wang, X Zhang, Z Zhu
Technometrics 65 (4), 514-523, 2023
6 2023 Prometheus: Taming Sample and Communication Complexities in Constrained Decentralized Stochastic Bilevel Learning Z Liu, X Zhang, P Khanduri, S Lu, J Liu
Proc. ICML 2023, 2023
6 2023 Communication-efficient network-distributed optimization with differential-coded compressors X Zhang, J Liu, Z Zhu, ES Bentley
IEEE INFOCOM 2020-IEEE Conference on Computer Communications, 317-326, 2020
5 2020