A Communication-Efficient Multi-Agent Actor-Critic Algorithm for Distributed Reinforcement Learning* Y Lin, K Zhang, Z Yang, Z Wang, T Başar, R Sandhu, J Liu 2019 IEEE 58th Conference on Decision and Control (CDC), 5562-5567, 2019 | 39 | 2019 |
Toward resilient multi-agent actor-critic algorithms for distributed reinforcement learning Y Lin, S Gade, R Sandhu, J Liu 2020 American Control Conference (ACC), 3953-3958, 2020 | 15 | 2020 |
Differentially private federated temporal difference learning Y Zeng, Y Lin, Y Yang, J Liu IEEE Transactions on Parallel and Distributed Systems 33 (11), 2714-2726, 2021 | 8 | 2021 |
Finite-time error bounds for distributed linear stochastic approximation Y Lin, V Gupta, J Liu Automatica 159, 111368, 2024 | 4 | 2024 |
Resilient Distributed Optimization* J Zhu, Y Lin, A Velasquez, J Liu 2023 American Control Conference (ACC), 1307-1312, 2023 | 4 | 2023 |
Subgradient-push is of the optimal convergence rate Y Lin, J Liu 2022 IEEE 61st Conference on Decision and Control (CDC), 5849-5856, 2022 | 4 | 2022 |
On a discrete-time network SIS model with opinion dynamics Y Lin, W Xuan, R Ren, J Liu 2021 60th IEEE Conference on Decision and Control (CDC), 2098-2103, 2021 | 4 | 2021 |
Resilient consensus-based multi-agent reinforcement learning with function approximation M Figura, Y Lin, J Liu, V Gupta arXiv preprint arXiv:2111.06776, 2021 | 4 | 2021 |
Reaching a consensus with limited information J Zhu, Y Lin, J Liu, AS Morse Systems & Control Letters 176, 105524, 2023 | 3 | 2023 |
Resilient constrained consensus over complete graphs via feasibility redundancy J Zhu, Y Lin, A Velasquez, J Liu 2022 American Control Conference (ACC), 3418-3422, 2022 | 2 | 2022 |
Resilient Consensus-based Multi-agent Reinforcement Learning M Figura, Y Lin, J Liu, V Gupta arXiv preprint arXiv:2111.06776, 2021 | 2 | 2021 |
Cooperative Actor-Critic via TD Error Aggregation M Figura, Y Lin, J Liu, V Gupta arXiv preprint arXiv:2207.12533, 2022 | 1 | 2022 |
An asynchronous multi-agent actor-critic algorithm for distributed reinforcement learning Y Lin, Y Luo, K Zhang, Z Yang, Z Wang, T Basar, R Sandhu, J Liu NeurIPS Optimization Foundations for Reinforcement Learning Workshop, 2019 | 1 | 2019 |
An Analysis Tool for Push-Sum Based Distributed Optimization Y Lin, J Liu arXiv preprint arXiv:2304.09443, 2023 | | 2023 |
Heterogeneous Distributed Subgradient Y Lin, J Liu arXiv preprint arXiv:2303.17060, 2023 | | 2023 |