A compressed gradient tracking method for decentralized optimization with linear convergence Y Liao, Z Li, K Huang, S Pu IEEE Transactions on Automatic Control 67 (10), 5622-5629, 2022 | 34 | 2022 |
Improving the transient times for distributed stochastic gradient methods K Huang, S Pu IEEE Transactions on Automatic Control 68 (7), 4127-4142, 2022 | 21 | 2022 |
Distributed random reshuffling over networks K Huang, X Li, A Milzarek, S Pu, J Qiu IEEE Transactions on Signal Processing 71, 1143-1158, 2023 | 12 | 2023 |
Distributed stochastic optimization under a general variance condition K Huang, X Li, S Pu IEEE Transactions on Automatic Control, 2024 | 5 | 2024 |
CEDAS: A compressed decentralized stochastic gradient method with improved convergence K Huang, S Pu arXiv preprint arXiv:2301.05872, 2023 | 3 | 2023 |
An accelerated distributed stochastic gradient method with momentum K Huang, S Pu, A Nedić arXiv preprint arXiv:2402.09714, 2024 | 2 | 2024 |
Distributed random reshuffling methods with improved convergence K Huang, L Zhou, S Pu arXiv preprint arXiv:2306.12037, 2023 | 1 | 2023 |