Tactics of adversarial attack on deep reinforcement learning agents YC Lin, ZW Hong, YH Liao, ML Shih, MY Liu, M Sun Proceedings of the 26th International Joint Conference on Artificial …, 2017 | 467 | 2017 |
Diversity-Driven Exploration Strategy for Deep Reinforcement Learning ZW Hong, TY Shann, SY Su, YH Chang, CY Lee Proceedings of the 32nd Conference on Neural Information Processing Systems, 2018 | 130 | 2018 |
A deep policy inference q-network for multi-agent systems ZW Hong, SY Su, TY Shann, YH Chang, CY Lee International Conference on Autonomous Agents and Multiagent Systems, 2017 | 119 | 2017 |
Virtual-to-Real: Learning to Control in Visual Semantic Segmentation ZW Hong, C Yu-Ming, SY Su, TY Shann, YH Chang, HK Yang, BHL Ho, ... Proceedings of the 27th International Joint Conference on Artificial …, 2018 | 91 | 2018 |
Stubborn: A strong baseline for indoor object navigation H Luo, A Yue, ZW Hong, P Agrawal 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2022 | 26 | 2022 |
Redeeming intrinsic rewards via constrained optimization E Chen, ZW Hong, J Pajarinen, P Agrawal Proceedings of the 36nd Conference on Neural Information Processing Systems, 2022 | 21 | 2022 |
Topological experience replay ZW Hong, T Chen, YC Lin, J Pajarinen, P Agrawal International Conference on Learning Representations 2022, 2022 | 17 | 2022 |
Harnessing mixed offline reinforcement learning datasets via trajectory weighting ZW Hong, P Agrawal, RT Combes, R Laroche International Conference on Learning Representations 2023, 2023 | 16 | 2023 |
Bilinear value networks ZW Hong, G Yang, P Agrawal International Conference on Learning Representations 2022, 2022 | 16* | 2022 |
Model-based lookahead reinforcement learning ZW Hong, J Pajarinen, J Peters arXiv preprint arXiv:1908.06012, 2019 | 12 | 2019 |
Curiosity-driven red-teaming for large language models ZW Hong, I Shenfeld, TH Wang, YS Chuang, A Pareja, J Glass, ... arXiv preprint arXiv:2402.19464, 2024 | 11 | 2024 |
Adversarial Active Exploration for Inverse Dynamics Model Learning ZW Hong, TJ Fu, TY Shann, YH Chang, CY Lee Proceedings of the 3rd Conference on Robot Learning, 2019 | 11* | 2019 |
Periodic intra-ensemble knowledge distillation for reinforcement learning ZW Hong, P Nagarajan, G Maeda Machine Learning and Knowledge Discovery in Databases. Research Track …, 2021 | 7* | 2021 |
Beyond Uniform Sampling: Offline Reinforcement Learning with Imbalanced Datasets ZW Hong, A Kumar, S Karnik, A Bhandwaldar, A Srivastava, J Pajarinen, ... Proceedings of the 37nd Conference on Neural Information Processing Systems, 2023 | 6 | 2023 |
Tgrl: An algorithm for teacher guided reinforcement learning I Shenfeld, ZW Hong, A Tamar, P Agrawal International Conference on Machine Learning, 31077-31093, 2023 | 5 | 2023 |
Tgrl: Teacher guided reinforcement learning algorithm for pomdps I Shenfeld, ZW Hong, A Tamar, P Agrawal Workshop on Reincarnating Reinforcement Learning at ICLR 2023, 2023 | 4 | 2023 |
Mixture of step returns in bootstrapped dqn PH Chiang, HK Yang, ZW Hong, CY Lee arXiv preprint arXiv:2007.08229, 2020 | 4 | 2020 |
Reducing the deployment-time inference control costs of deep reinforcement learning agents via an asymmetric architecture CJ Chang, YW Chu, CH Ting, HK Liu, ZW Hong, CY Lee 2021 IEEE International Conference on Robotics and Automation (ICRA), 4762-4768, 2021 | 3 | 2021 |
Neuro-Inspired Fragmentation and Recall to Overcome Catastrophic Forgetting in Curiosity J Hwang, ZW Hong, E Chen, A Boopathy, P Agrawal, I Fiete arXiv preprint arXiv:2310.17537, 2023 | 2 | 2023 |
Parallel -Learning: Scaling Off-policy Reinforcement Learning under Massively Parallel Simulation Z Li, T Chen, ZW Hong, A Ajay, P Agrawal International Conference on Machine Learning, 19440-19459, 2023 | 2 | 2023 |