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
412 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
110 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
105 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
80 2018 Bilinear value networks ZW Hong, G Yang, P Agrawal
International Conference on Learning Representations 2022, 2022
14 * 2022 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
13 2022 Topological experience replay ZW Hong, T Chen, YC Lin, J Pajarinen, P Agrawal
International Conference on Learning Representations 2022, 2022
11 2022 Model-based lookahead reinforcement learning ZW Hong, J Pajarinen, J Peters
arXiv preprint arXiv:1908.06012, 2019
11 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
10 * 2019 Harnessing mixed offline reinforcement learning datasets via trajectory weighting ZW Hong, P Agrawal, RT Combes, R Laroche
International Conference on Learning Representations 2023, 2023
6 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
6 * 2021 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
4 2022 Mixture of step returns in bootstrapped dqn PH Chiang, HK Yang, ZW Hong, CY Lee
arXiv preprint arXiv:2007.08229, 2020
3 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
2 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
1 2023 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
1 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
1 2023 Neuro-Inspired Efficient Map Building via Fragmentation and Recall J Hwang, ZW Hong, E Chen, A Boopathy, P Agrawal, I Fiete
arXiv preprint arXiv:2307.05793, 2023
2023 Parallel Z Li, T Chen, ZW Hong, A Ajay, P Agrawal
International Conference on Machine Learning, 19440-19459, 2023
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
2023 
Chun-Yi LeeDepartment of Computer Science, National Tsing Hua UniversityBestätigte E-Mail-Adresse bei cs.nthu.edu.tw
