| Who Is the Strongest Enemy? Towards Optimal and Efficient Evasion Attacks in Deep RL Y Sun, R Zheng, Y Liang, F Huang The 10th International Conference on Learning Representations (ICLR 2022), 2022 | 76 | 2022 |
| Vulnerability-Aware Poisoning Mechanism for Online RL with Unknown Dynamics Y Sun, D Huo, F Huang 9th International Conference on Learning Representations (ICLR 2021)., 2021 | 57 | 2021 |
| Efficient Adversarial Training without Attacking: Worst-Case-Aware Robust Reinforcement Learning Y Liang, Y Sun, R Zheng, F Huang The 36th Conference on Neural Information Processing Systems (NeurIPS) 2022, 2022 | 55 | 2022 |
| SMART: Self-supervised Multi-task pretrAining with contRol Transformers Y Sun, S Ma, R Madaan, R Bonatti, F Huang, A Kapoor International Conference on Learning Representations (ICLR) 2023, 2023 | 46 | 2023 |
| : Temporal Latent Action-Driven Contrastive Loss for Visual Reinforcement Learning R Zheng, X Wang, Y Sun, S Ma, J Zhao, H Xu, H Daumé III, F Huang Advances in Neural Information Processing Systems 36, 48203-48225, 2023 | 43 | 2023 |
| Exploring and exploiting decision boundary dynamics for adversarial robustness Y Xu, Y Sun, M Goldblum, T Goldstein, F Huang arXiv preprint arXiv:2302.03015, 2023 | 40 | 2023 |
| Understanding generalization in deep learning via tensor methods J Li, Y Sun, J Su, T Suzuki, F Huang International Conference on Artificial Intelligence and Statistics, 504-515, 2020 | 33 | 2020 |
| Temple: Learning template of transitions for sample efficient multi-task RL Y Sun, X Yin, F Huang 35th AAAI Conference on Artificial Intelligence (AAAI 2021)., 2021 | 24 | 2021 |
| Transfer RL across Observation Feature Spaces via Model-Based Regularization Y Sun, R Zheng, X Wang, A Cohen, F Huang The 10th International Conference on Learning Representations (ICLR 2022), 2022 | 21 | 2022 |
| Certifiably robust policy learning against adversarial multi-agent communication Y Sun, R Zheng, P Hassanzadeh, Y Liang, S Feizi, S Ganesh, F Huang The Eleventh International Conference on Learning Representations, 2022 | 20 | 2022 |
| Is imitation all you need? generalized decision-making with dual-phase training Y Wei, Y Sun, R Zheng, S Vemprala, R Bonatti, S Chen, R Madaan, Z Ba, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 17 | 2023 |
| Instructed diffuser with temporal condition guidance for offline reinforcement learning J Hu, Y Sun, S Huang, SY Guo, H Chen, L Shen, L Sun, Y Chang, D Tao arXiv preprint arXiv:2306.04875, 2023 | 14 | 2023 |
| Certifiably Robust Policy Learning against Adversarial Communication in Multi-agent Systems Y Sun, R Zheng, P Hassanzadeh, Y Liang, S Feizi, S Ganesh, F Huang International Conference on Learning Representations (ICLR) 2023, 2023 | 13 | 2023 |
| A simple unified uncertainty-guided framework for offline-to-online reinforcement learning S Guo, Y Sun, J Hu, S Huang, H Chen, H Piao, L Sun, Y Chang arXiv preprint arXiv:2306.07541, 2023 | 11 | 2023 |
| Distributional Reward Estimation for Effective Multi-Agent Deep Reinforcement Learning J Hu, Y Sun, H Chen, S Huang, Y Chang, L Sun Advances in Neural Information Processing Systems (NeurIPS), 2022, 2022 | 11 | 2022 |
| Adversarial Auto-Augment with Label Preservation: A Representation Learning Principle Guided Approach K Yang, Y Sun, J Su, F He, X Tian, F Huang, T Zhou, D Tao Advances in Neural Information Processing Systems (NeurIPS), 2022, 2022 | 10 | 2022 |
| Learning generalizable agents via saliency-guided features decorrelation S Huang, Y Sun, J Hu, S Guo, H Chen, Y Chang, L Sun, B Yang Advances in Neural Information Processing Systems 36, 39363-39381, 2023 | 9 | 2023 |
| Coplanner: Plan to roll out conservatively but to explore optimistically for model-based rl X Wang, R Zheng, Y Sun, R Jia, W Wongkamjan, H Xu, F Huang arXiv preprint arXiv:2310.07220, 2023 | 8 | 2023 |
| Collaborative inference of coexisting information diffusions Y Sun, C Qian, N Yang, SY Philip 2017 IEEE International Conference on Data Mining (ICDM), 1093-1098, 2017 | 8 | 2017 |
| Game-theoretic robust reinforcement learning handles temporally-coupled perturbations Y Liang, Y Sun, R Zheng, X Liu, B Eysenbach, T Sandholm, F Huang, ... arXiv preprint arXiv:2307.12062, 2023 | 6 | 2023 |
Furong HuangAssociate Professor of Computer Science, University of MarylandPotvrđena adresa e-pošte na umd.edu