| Filter design for generalized frequency-division multiplexing S Han, Y Sung, YH Lee IEEE Transactions on Signal Processing 65 (7), 1644-1659, 2016 | 68 | 2016 |
| Dimension-wise importance sampling weight clipping for sample-efficient reinforcement learning S Han, Y Sung International Conference on Machine Learning, 2586-2595, 2019 | 24 | 2019 |
| Diversity actor-critic: Sample-aware entropy regularization for sample-efficient exploration S Han, Y Sung International Conference on Machine Learning, 4018-4029, 2021 | 23 | 2021 |
| A max-min entropy framework for reinforcement learning S Han, Y Sung Advances in Neural Information Processing Systems 34, 25732-25745, 2021 | 17 | 2021 |
| Robust imitation learning against variations in environment dynamics J Chae, S Han, W Jung, M Cho, S Choi, Y Sung International Conference on Machine Learning, 2828-2852, 2022 | 13 | 2022 |
| A reinforcement learning formulation of the lyapunov optimization: Application to edge computing systems with queue stability S Bae, S Han, Y Sung arXiv preprint arXiv:2012.07279, 2020 | 13 | 2020 |
| Amber: Adaptive multi-batch experience replay for continuous action control S Han, Y Sung IJCAI Workshop on Scaling Up Reinforcement Learning, 2017 | 9* | 2017 |
| Domain adaptive imitation learning with visual observation S Choi, S Han, W Kim, J Chae, W Jung, Y Sung Advances in Neural Information Processing Systems 36, 2024 | 7* | 2024 |
| FoX: Formation-aware exploration in multi-agent reinforcement learning Y Jo, S Lee, J Yeom, S Han Proceedings of the AAAI Conference on Artificial Intelligence 38 (12), 12985 …, 2024 | 2 | 2024 |
| Exclusively Penalized Q-learning for Offline Reinforcement Learning J Yeom, Y Jo, J Kim, S Lee, S Han arXiv preprint arXiv:2405.14082, 2024 | | 2024 |
| Off-policy multi-agent policy optimization with multi-step counterfactual advantage estimation S Kim, W Kim, J Jeon, Y Sung, S Han The 22nd International Conference on Autonomous Agents and Multiagent …, 2023 | | 2023 |
| Novel entropy frameworks for sample-efficient exploration in off-policy reinforcement learning S Han 한국과학기술원, 2021 | | 2021 |
| Adaptive Multi-model Fusion Learning for Sparse-Reward Reinforcement Learning G Park, W Jung, S Han, S Choi, Y Sung Available at SSRN 4850588, 0 | | |
