| OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation J Lee, W Jeon, BJ Lee, J Pineau, KE Kim ICML, 2021 | 92 | 2021 |
| DemoDICE: Offline Imitation Learning with Supplementary Imperfect Demonstrations GH Kim, S Seo, J Lee, W Jeon, HJ Hwang, H Yang, KE Kim International Conference on Learning Representations (ICLR), 2022 | 74 | 2022 |
| Monte-Carlo Tree Search for Constrained POMDPs J Lee, GH Kim, P Poupart, KE Kim NeurIPS, 2018 | 74 | 2018 |
| Multi-view automatic lip-reading using neural network D Lee, J Lee, KE Kim Computer Vision–ACCV 2016 Workshops: ACCV 2016 International Workshops …, 2017 | 62 | 2017 |
| Representation balancing offline model-based reinforcement learning BJ Lee, J Lee, KE Kim International Conference on Learning Representations (ICLR), 2021 | 50 | 2021 |
| GPT-Critic: Offline Reinforcement Learning for End-to-End Task-Oriented Dialogue Systems Y Jang, J Lee, KE Kim International Conference on Learning Representations (ICLR), 2022 | 48 | 2022 |
| COptiDICE: Offline Constrained Reinforcement Learning via Stationary Distribution Correction Estimation J Lee, C Paduraru, DJ Mankowitz, N Heess, D Precup, KE Kim, A Guez International Conference on Learning Representations (ICLR), 2022 | 35 | 2022 |
| Bayes-Adaptive Monte-Carlo Planning and Learning for Goal-Oriented Dialogues Y Jang, J Lee, KE Kim AAAI, 2020 | 25 | 2020 |
| Monte-Carlo Tree Search in Continuous Action Spaces with Value Gradients J Lee, W Jeon, GH Kim, KE Kim AAAI, 2020 | 23 | 2020 |
| Reinforcement Learning for Control with Multiple Frequencies J Lee, BJ Lee, KE Kim Advances in Neural Information Processing Systems (NeurIPS) 33, 2020 | 18 | 2020 |
| Batch Reinforcement Learning with Hyperparameter Gradients BJ Lee, J Lee, P Vrancx, D Kim, KE Kim ICML, 2020 | 18 | 2020 |
| Hierarchically-partitioned Gaussian Process Approximation BJ Lee, J Lee, KE Kim Artificial Intelligence and Statistics (AISTATS), 822-831, 2017 | 17 | 2017 |
| PyOpenDial: a python-based domain-independent toolkit for developing spoken dialogue systems with probabilistic rules Y Jang, J Lee, J Park, KH Lee, P Lison, KE Kim Proceedings of the 2019 conference on empirical methods in natural language …, 2019 | 11 | 2019 |
| Constrained Bayesian Reinforcement Learning via Approximate Linear Programming J Lee, Y Jang, P Poupart, KE Kim IJCAI, 2088-2095, 2017 | 11 | 2017 |
| Monte-carlo planning and learning with language action value estimates Y Jang, S Seo, J Lee, KE Kim International Conference on Learning Representations (ICLR), 2021 | 9 | 2021 |
| LobsDICE: Offline Imitation Learning from Observation via Stationary Distribution Correction Estimation GH Kim, J Lee, Y Jang, H Yang, KE Kim Advances in Neural Information Processing Systems (NeurIPS), 2022 | 7 | 2022 |
| Tempo Adaption in Non-stationary Reinforcement Learning H Lee, Y Ding, J Lee, M Jin, J Lavaei, S Sojoudi Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), 2023 | 3 | 2023 |
| Local Metric Learning for Off-Policy Evaluation in Contextual Bandits with Continuous Actions H Lee, J Lee, Y Choi, W Jeon, BJ Lee, YK Noh, KE Kim Advances in Neural Information Processing Systems (NeurIPS), 2022 | 3 | 2022 |
| Trust Region Sequential Variational Inference GH Kim, Y Jang, J Lee, W Jeon, H Yang, KE Kim Asian Conference on Machine Learning (ACML), 1033-1048, 2019 | 2 | 2019 |
| Layered Behavior Modeling via Combining Descriptive and Prescriptive Approaches: A Case Study of Infantry Company Engagement JW Bae, J Lee, DH Kim, K Lee, J Lee, KE Kim, IC Moon IEEE Transactions on Systems, Man, and Cybernetics: Systems 50 (7), 2551-2565, 2018 | 2 | 2018 |
Kee-Eung KimKAIST在 kaist.ac.kr 的电子邮件经过验证
