| Efficient Average Reward Reinforcement Learning Using Constant Shifting Values S Yang, Y Gao, B An, H Wang, X Chen Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016 | 30 | 2016 |
| An Optimal Algorithm for the Stochastic Bandits While Knowing the Near-Optimal Mean Reward S Yang, Y Gao IEEE Transactions on Neural Networks and Learning Systems 32 (5), 2285-2291, 2021 | 11 | 2021 |
| A Contextual Bandit Approach to Personalized Online Recommendation via Sparse Interactions C Zhang, H Wang, S Yang, Y Gao Advances in Knowledge Discovery and Data Mining: 23rd Pacific-Asia …, 2019 | 11 | 2019 |
| Contextual Bandits With Hidden Features to Online Recommendation via Sparse Interactions S Yang, H Wang, C Zhang, Y Gao IEEE Intelligent Systems 35 (5), 62-72, 2020 | 8 | 2020 |
| New Galois Hulls Of Generalized Reed-Solomon Codes Y Wu, C Li, S Yang Finite Fields and Their Applications 83, 102084, 2022 | 7 | 2022 |
| Incremental Nonnegative Matrix Factorization Based on Matrix Sketching and k-means Clustering C Zhang, H Wang, S Yang, Y Gao Intelligent Data Engineering and Automated Learning–IDEAL 2016: 17th …, 2016 | 5 | 2016 |
| Effective Interpretable Policy Distillation via Critical Experiences Identification X Liu, S Liu, B An, Y Gao, S Yang, W Li IEEE Intelligent Systems, 2023 | 4 | 2023 |
| Modified Retrace for Off-Policy Temporal Difference Learning X Chen, X Ma, Y Li, G Yang, S Yang, Y Gao 39th Conference On Uncertainty in Artificial Intelligence, 2023 | 2 | 2023 |
| Learning Explicit Credit Assignment for Cooperative Multi-Agent Reinforcement Learning via Polarization Policy Gradient W Chen, W Li, X Liu, S Yang, Y Gao Proceedings of the AAAI Conference on Artificial Intelligence, 2023 | 2 | 2023 |
| Keeping Minimal Experience to Achieve Efficient Interpretable Policy Distillation X Liu, S Liu, W Li, S Yang, Y Gao arXiv preprint arXiv:2203.00822, 2022 | 2 | 2022 |
| An Optimal Algorithm for the Stochastic Bandits with Knowing Near-optimal Mean Reward S Yang, H Wang, Y Gao, X Chen Proceedings of the 17th International Conference on Autonomous Agents and …, 2018 | 2 | 2018 |
| WToE: Learning When to Explore in Multi-Agent Reinforcement Learning S Dong, H Mao, S Yang, Z Shengyu, L Wenbin, H Jianye, Y Gao IEEE Transactions on Cybernetics, 2023 | 1 | 2023 |
| Modeling rationality: Toward better performance against unknown agents in sequential games Z Ge, S Yang, P Tian, Z Chen, Y Gao IEEE Transactions on Cybernetics, 2022 | 1 | 2022 |
| Online attentive kernel-based temporal difference learning G Yang, X Chen, S Yang, H Wang, S Dong, Y Gao arXiv preprint arXiv:2201.09065, 2022 | 1 | 2022 |
| Learning Credit Assignment for Cooperative Reinforcement Learning W Chen, W Li, X Liu, S Yang arXiv preprint arXiv:2210.05367, 2022 | 1 | 2022 |
| Multi-Agent Sparse Interaction Modeling is an Anomaly Detection Problem C Li, S Dong, S Yang, H Cao, W Li, Y Gao ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2024 | | 2024 |
| Online attentive kernel-based temporal difference learning X Chen, G Yang, S Yang, H Wang, S Dong, Y Gao Knowledge-Based Systems 278, 110902, 2023 | | 2023 |
| Enhancing OOD Generalization in Offline Reinforcement Learning with Energy-Based Policy Optimization H Cao, S Yang, J Huo, X Chen, Y Gao 26th European Conference on Artificial Intelligence ECAI 2023, 2023 | | 2023 |
| Convergence Analysis of Graphical Game-based Nash Q−learning Using the Interaction Detection Signal of N−step Return Y Zhuang, S Yang, W Li, Y Gao 2023 IEEE International Conference on Acoustics, Speech and Signal Processing, 2023 | | 2023 |
| Leveraging transition exploratory bonus for efficient exploration in Hard-Transiting reinforcement learning problems S Yang, H Wang, S Dong, X Chen Future Generation Computer Systems, 2023 | | 2023 |
Yang GaoNanjing University, ChinaVerified email at nju.edu.cn
