| Pareto: Fair congestion control with online reinforcement learning S Emara, F Wang, B Li, T Zeyl IEEE Transactions on Network Science and Engineering 9 (5), 3731-3748, 2022 | 14 | 2022 |
| More than enough is too much: Adaptive defenses against gradient leakage in production federated learning F Wang, E Hugh, B Li IEEE/ACM Transactions on Networking, 2024 | 11 | 2024 |
| Federated unlearning and its privacy threats F Wang, B Li, B Li IEEE Network, 2023 | 9 | 2023 |
| Plato: An open-source research framework for production federated learning B Li, N Su, C Ying, F Wang Proceedings of the ACM Turing Award Celebration Conference-China 2023, 1-2, 2023 | 4 | 2023 |
| Ivory: Learning network adaptive streaming codes S Emara, F Wang, I Kaplan, B Li 2022 IEEE/ACM 30th International Symposium on Quality of Service (IWQoS), 1-10, 2022 | 2 | 2022 |
| Quality-oriented federated learning on the fly F Wang, B Li, B Li IEEE Network 36 (5), 152-159, 2022 | 1 | 2022 |
| Method and apparatus for multiple reinforcement learning agents in a shared environment Z Hu, TJ Zeyl, SSHM Emara, B Li, F Wang US Patent App. 17/566,953, 2023 | | 2023 |
| Multi-Agent Deep Reinforcement Learning for Cooperative Edge Caching via Hybrid Communication F Wang, S Emara, I Kaplan, B Li, T Zeyl ICC 2023-IEEE International Conference on Communications, 1206-1211, 2023 | | 2023 |
| Cascade: Enhancing Reinforcement Learning with Curriculum Federated Learning and Interference Avoidance—A Case Study in Adaptive Bitrate Selection S Emara, D Liu, F Wang, B Li | | |
Baochun LiProfessor of Electrical and Computer Engineering, University of TorontoVerified email at ece.toronto.edu
