Byzantine-robust decentralized stochastic optimization over static and time-varying networks J Peng, W Li, Q Ling Signal Processing 183, 108020, 2021 | 37 | 2021 |
Communication-censored linearized ADMM for decentralized consensus optimization W Li, Y Liu, Z Tian, Q Ling IEEE Transactions on Signal and Information Processing over Networks 6, 18-34, 2019 | 25 | 2019 |
COLA: Communication-censored linearized ADMM for decentralized consensus optimization W Li, Y Liu, Z Tian, Q Ling ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 16 | 2019 |
Communication-censored distributed stochastic gradient descent W Li, Z Wu, T Chen, L Li, Q Ling IEEE Transactions on Neural Networks and Learning Systems 33 (11), 6831-6843, 2021 | 14 | 2021 |
Variance reduction-boosted Byzantine robustness in decentralized stochastic optimization J Peng, W Li, Q Ling ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 7 | 2022 |
On the optimal control of network LQR with spatially-exponential decaying structure RC Zhang, W Li, N Li 2023 American Control Conference (ACC), 1775-1780, 2023 | 6 | 2023 |
On the relationship of optimal state feedback and disturbance response controllers RC Zhang, Y Zheng, W Li, N Li IFAC-PapersOnLine 56 (2), 7503-7508, 2023 | 2 | 2023 |
Stochastic alternating direction method of multipliers for Byzantine-robust distributed learning F Lin, W Li, Q Ling Signal Processing 195, 108501, 2022 | 2 | 2022 |
Stochastic alternating direction method of multipliers for byzantine-robust distributed learning F Lin, W Li, Q Ling arXiv preprint arXiv:2106.06891, 2021 | 2 | 2021 |
Stochastic Admm for Byzantine-robust distributed learning F Lin, Q Ling, W Li, Z Xiong ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 2 | 2020 |
Byzantine-robust decentralized stochastic optimization with stochastic gradient noise-independent learning error J Peng, W Li, Q Ling Signal Processing, 109419, 2024 | 1 | 2024 |
Best subset selection in reduced rank regression C Wen, R Dong, X Wang, W Li, H Zhang arXiv preprint arXiv:2211.15889, 2022 | 1 | 2022 |