| Learning efficient multi-agent communication: An information bottleneck approach R Wang, X He, R Yu, W Qiu, B An, Z Rabinovich International Conference on Machine Learning, 9908-9918, 2020 | 117 | 2020 |
| Personalized adaptive meta learning for cold-start user preference prediction R Yu, Y Gong, X He, Y Zhu, Q Liu, W Ou, B An Proceedings of the AAAI conference on artificial intelligence 35 (12), 10772 …, 2021 | 75 | 2021 |
| 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 | 60 | 2021 |
| 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 | 40 | 2020 |
| Dynamically expandable graph convolution for streaming recommendation B He, X He, Y Zhang, R Tang, C Ma Proceedings of the ACM Web Conference 2023, 1457-1467, 2023 | 35 | 2023 |
| 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 | 26 | 2022 |
| Contextual user browsing bandits for large-scale online mobile recommendation X He, B An, Y Li, H Chen, Q Guo, X Li, Z Wang Proceedings of the 14th ACM Conference on Recommender Systems, 63-72, 2020 | 16 | 2020 |
| Dynamic Embedding Size Search with Minimum Regret for Streaming Recommender System B He, X He, R Zhang, Y Zhang, R Tang, C Ma Proceedings of the 32nd ACM International Conference on Information and …, 2023 | 14 | 2023 |
| Learning behaviors with uncertain human feedback X He, H Chen, B An Conference on Uncertainty in Artificial Intelligence, 131-140, 2020 | 8 | 2020 |
| 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 |
| RMIX: Risk-sensitive multi-agent reinforcement learning W Qiu, X Wang, R Yu, X He, R Wang, B An, S Obraztsova, Z Rabinovich | 2 | 2020 |
| Context-aware multi-agent coordination with loose couplings and repeated interaction F Lin, X He, B An Distributed Artificial Intelligence: Second International Conference, DAI …, 2020 | 1 | 2020 |
| Re-examining Supervised Dimension Reduction for High-Dimensional Bayesian Optimization Q Chen, J Huo, Y Chen, T Ding, Y Gao, D Li, X He International Conference on Parallel Problem Solving from Nature, 356-373, 2024 | | 2024 |
| Resultant: Incremental Effectiveness on Likelihood for Unsupervised Out-of-Distribution Detection Y Li, C Wang, X Xia, X He, R An, D Li, T Liu, B An, X Wang arXiv preprint arXiv:2409.03801, 2024 | | 2024 |
| PoRank: A Practical Framework for Learning to Rank Policies P Gu, M Zhao, X He, Y Cai, B An Proceedings of the Thirty-Third International Joint Conference on Artificial …, 2024 | | 2024 |
| Improving Unsupervised Hierarchical Representation with Reinforcement Learning R An, Y Li, X He, P Gu, M Zhao, D Li, J Hao, C Wang, B An, M Zhou Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | | 2024 |
| Recommendation via reinforcement learning methods H Xu Nanyang Technological University, 2021 | | 2021 |
| Towards Complete Expressiveness Capacity of Mixed Multi-Agent Q Value Function L Wan, X He, Z Liu, K Li, X Chen, M Zhao, D Li, B An, X Lan | | |
| Representation Interference Suppression via Non-linear Value Factorization for Indecomposable Markov Games L Wan, X He, Z Liu, K Li, M Zhao, D Li, B An, HAO Jianye, X Lan | | |
Bo AnNanyang Technological UniversityVerified email at ntu.edu.sg