Learning Efficient Multi-agent Communication: An Information Bottleneck Approach R Wang, X He, R Yu, W Qiu, B An, Z Rabinovich (ICML 2020) 37th International Conference on Machine Learning, 2020 | 92 | 2020 |
Rmix: Learning risk-sensitive policies for cooperative reinforcement learning agents W Qiu, X Wang, R Yu, R Wang, X He, B An, S Obraztsova, Z Rabinovich Advances in Neural Information Processing Systems 34, 23049-23062, 2021 | 47 | 2021 |
Reinforcement learning for quantitative trading S Sun, R Wang, B An ACM Transactions on Intelligent Systems and Technology 14 (3), 1-29, 2023 | 38 | 2023 |
Learning to collaborate in multi-module recommendation via multi-agent reinforcement learning without communication X He, B An, Y Li, H Chen, R Wang, X Wang, R Yu, X Li, Z Wang Proceedings of the 14th ACM Conference on Recommender Systems, 210-219, 2020 | 36 | 2020 |
Commission fee is not enough: A hierarchical reinforced framework for portfolio management R Wang, H Wei, B An, Z Feng, J Yao Proceedings of the AAAI Conference on Artificial Intelligence 35 (1), 626-633, 2021 | 33 | 2021 |
Transferable Environment Poisoning: Training-time Attack on Reinforcement Learning H Xu, R Wang, L Raizman, Z Rabinovich 20th International Conference on Autonomous Agents and Multiagent Systems, 2021 | 28 | 2021 |
I^2 HRL: Interactive Influence-based Hierarchical Reinforcement Learning R Wang, R Yu, B An, Z Rabinovich (IJCAI-PRICAI 2020) The 29th International Joint Conference on Artificial …, 2020 | 24 | 2020 |
Deep reinforcement learning for quantitative trading: Challenges and opportunities B An, S Sun, R Wang IEEE Intelligent Systems 37 (2), 23-26, 2022 | 21 | 2022 |
Learning expensive coordination: An event-based deep RL approach Z Shi, R Yu, X Wang, R Wang, Y Zhang, H Lai, B An International Conference on Learning Representations, 2019 | 14 | 2019 |
DeepScalper: A risk-aware reinforcement learning framework to capture fleeting intraday trading opportunities S Sun, W Xue, R Wang, X He, J Zhu, J Li, B An Proceedings of the 31st ACM International Conference on Information …, 2022 | 11 | 2022 |
Attention over self-attention: Intention-aware re-ranking with dynamic transformer encoders for recommendation Z Lin, S Zang, R Wang, Z Sun, J Senthilnath, C Xu, CK Kwoh IEEE Transactions on Knowledge and Data Engineering, 2022 | 9 | 2022 |
Synapse: Trajectory-as-exemplar prompting with memory for computer control L Zheng, R Wang, X Wang, B An The Twelfth International Conference on Learning Representations, 2023 | 8 | 2023 |
Synapse: Leveraging few-shot exemplars for human-level computer control L Zheng, R Wang, B An arXiv preprint arXiv:2306.07863, 2023 | 8 | 2023 |
Towards skilled population curriculum for multi-agent reinforcement learning R Wang, L Zheng, W Qiu, B He, B An, Z Rabinovich, Y Hu, Y Chen, T Lv, ... arXiv preprint arXiv:2302.03429, 2023 | 6 | 2023 |
Towards effective and interpretable human-agent collaboration in moba games: A communication perspective Y Gao, F Liu, L Wang, Z Lian, W Wang, S Li, X Wang, X Zeng, R Wang, ... arXiv preprint arXiv:2304.11632, 2023 | 5 | 2023 |
Metainfonet: Learning task-guided information for sample reweighting H Wei, L Feng, R Wang, B An arXiv preprint arXiv:2012.05273, 2020 | 5 | 2020 |
Deep stock trading: A hierarchical reinforcement learning framework for portfolio optimization and order execution R Wang, H Wei, B An, Z Feng, J Yao arXiv preprint arXiv:2012.12620, 2020 | 4 | 2020 |
Inducing cooperation via team regret minimization based multi-agent deep reinforcement learning R Yu, Z Shi, X Wang, R Wang, B Liu, X Hou, H Lai, B An arXiv preprint arXiv:1911.07712, 2019 | 4 | 2019 |
Deepscalper: A risk-aware deep reinforcement learning framework for intraday trading with micro-level market embedding S Sun, R Wang, X He, J Zhu, J Li, B An arXiv preprint arXiv:2201.09058, 2022 | 3 | 2022 |
Defensive compressive time delay estimation using information bottleneck Y Li, R Wang, Y Hu, J Yang, X Cai IEEE Signal Processing Letters 28, 1968-1972, 2021 | 3 | 2021 |