| Push–pull gradient methods for distributed optimization in networks S Pu, W Shi, J Xu, A Nedić IEEE Transactions on Automatic Control 66 (1), 1-16, 2020 | 427 | 2020 |
| Augmented distributed gradient methods for multi-agent optimization under uncoordinated constant stepsizes J Xu, S Zhu, YC Soh, L Xie 2015 IEEE 54th Annual Conference on Decision and Control (CDC), 2055-2060, 2015 | 380 | 2015 |
| Convergence of Asynchronous Distributed Gradient Methods over Stochastic Networks J Xu, S Zhu, YC Soh, L Xie IEEE Transactions on Automatic Control 63 (2), 434-448, 2018 | 227 | 2018 |
| Modeling regular occupancy in commercial buildings using stochastic models Z Chen, J Xu, YC Soh Energy and Buildings 103, 216-223, 2015 | 106 | 2015 |
| Distributed algorithms for composite optimization: Unified framework and convergence analysis J Xu, Y Tian, Y Sun, G Scutari IEEE Transactions on Signal Processing 69, 3555 - 3570, 2021 | 101 | 2021 |
| Privacy Preserving Distributed Online Optimization over Unbalanced Digraphs via Subgradient Rescaling Y Xiong, J Xu, K You, J Liu, L Wu IEEE Transactions on Control of Network Systems, 2020 | 79 | 2020 |
| A Bregman splitting scheme for distributed optimization over networks J Xu, S Zhu, YC Soh, L Xie IEEE Transactions on Automatic Control 63 (11), 3809-3824, 2018 | 55 | 2018 |
| A dual splitting approach for distributed resource allocation with regularization J Xu, S Zhu, YC Soh, L Xie IEEE Transactions on Control of Network Systems 6 (1), 403-414, 2019 | 47 | 2019 |
| Accelerated primal-dual algorithms for distributed smooth convex optimization over networks J Xu, Y Tian, Y Sun, G Scutari International Conference on Artificial Intelligence and Statistics (AISTATS …, 2020 | 45 | 2020 |
| Mitigating Quantization Effects on Distributed Sensor Fusion: A Least Squares Approach S Zhu, C Chen, J Xu, X Guan, L Xie, KH Johansson IEEE Transactions on Signal Processing 66 (13), 3459-3474, 2018 | 39 | 2018 |
| Differentially Private Distributed Resource Allocation via Deviation Tracking T Ding, S Zhu, C Chen, J Xu, X Guan IEEE Transactions on Signal and Information Processing over Networks 7, 222-235, 2021 | 31 | 2021 |
| Tackling Data Heterogeneity: A New Unified Framework for Decentralized SGD with Sample-induced Topology Y Huang, Y Sun, Z Zhu, C Yan, J Xu International Conference on Machine Learning (ICML 2022), 9310-9345, 2022 | 19 | 2022 |
| A distributed simultaneous perturbation approach for large-scale dynamic optimization problems J Xu, YC Soh Automatica 72, 194-204, 2016 | 19 | 2016 |
| Distributed extremum seeking control of networked large-scale systems under constraints J Xu, YC Soh 2013 IEEE 52nd Annual Conference on Decision and Control (CDC), 2187-2192, 2013 | 17 | 2013 |
| Lithography hotspot detection via heterogeneous federated learning with local adaptation X Lin, J Pan, J Xu, Y Chen, C Zhuo 2022 27th Asia and South Pacific Design Automation Conference (ASP-DAC), 166-171, 2022 | 10 | 2022 |
| A unified algorithmic framework for distributed composite optimization J Xu, Y Tian, Y Sun, G Scutari 2020 59th IEEE Conference on Decision and Control (CDC), 2309-2316, 2020 | 10 | 2020 |
| A dual splitting method for distributed economic dispatch in multi-energy systems Z Wang, J Xu, S Zhu, C Chen IFAC-PapersOnLine 53 (2), 12566-12571, 2020 | 9 | 2020 |
| A unified contraction analysis of a class of distributed algorithms for composite optimization J Xu, Y Sun, Y Tian, G Scutari 2019 IEEE 8th International Workshop on Computational Advances in Multi …, 2019 | 8 | 2019 |
| A forward-backward Bregman splitting scheme for regularized distributed optimization problems J Xu, S Zhu, YC Soh, L Xie 2016 IEEE 55th Annual Conference on Decision and Control (CDC), 1093-1098, 2016 | 7 | 2016 |
| Augmented distributed optimization for networked systems J Xu Nanyang Technological University, 2016 | 7 | 2016 |
Shanying ZhuDepartment of Automation, Shanghai Jiao Tong UniversityVerified email at sjtu.edu.cn