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
516 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
147 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
135 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
95 2018 Curiosity-driven red-teaming for large language models ZW Hong, I Shenfeld, TH Wang, YS Chuang, A Pareja, J Glass, ...
International Conference on Learning Representations 2024, 2024
51 2024 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
42 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
35 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
22 2023 Topological experience replay ZW Hong, T Chen, YC Lin, J Pajarinen, P Agrawal
International Conference on Learning Representations 2022, 2022
21 2022 Tgrl: An algorithm for teacher guided reinforcement learning I Shenfeld, ZW Hong, A Tamar, P Agrawal
International Conference on Machine Learning, 31077-31093, 2023
20 * 2023 Bilinear value networks ZW Hong, G Yang, P Agrawal
International Conference on Learning Representations 2022, 2022
19 * 2022 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
15 2023 Model-based lookahead reinforcement learning ZW Hong, J Pajarinen, J Peters
arXiv preprint arXiv:1908.06012, 2019
14 2019 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
12 * 2019 Model Predictive Control via On-Policy Imitation Learning K Ahn, Z Mhammedi, H Mania, ZW Hong, A Jadbabaie
4th Annual Learning for Dynamics & Control Conference, 2022
10 2022 Parallel Z Li, T Chen, ZW Hong, A Ajay, P Agrawal
International Conference on Machine Learning, 19440-19459, 2023
9 2023 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 Mixture of step returns in bootstrapped dqn PH Chiang, HK Yang, ZW Hong, CY Lee
arXiv preprint arXiv:2007.08229, 2020
5 2020 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
4 2023 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 
Pulkit AgrawalMassachusetts Institute of TechnologyZweryfikowany adres z mit.edu