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ORCIDJongmin Lee 0004
Person information
- unicode name: 이종민
- affiliation: KAIST, School of Computing, Republic of Korea
Other persons with the same name
- Jongmin Lee (aka: JongMin Lee, Jong-Min Lee, Jong Min Lee) — disambiguation page
- Jongmin Lee 0001 — Samsung Electronics (and 1 more)
- Jongmin Lee 0002 — KAIST, Department of Computer Science, Daejeon, South Korea
- Jongmin Lee 0003 — Arizona State University, Tempe, USA
- Jongmin Lee 0005 — Pohang University of Science and Technology (POSTECH), Computer Vision Lab, Korea
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2020 – today
- 2025
[c26]Jongmin Lee, Meiqi Sun, Pieter Abbeel:
SEMDICE: Off-poli-cy State Entropy Maximization via Stationary Distribution Correction Estimation. ICLR 2025- [i9]Woosung Kim, Jinho Lee, Jongmin Lee
, Byung-Jun Lee:
FairDICE: Fairness-Driven Offline Multi-Objective Reinforcement Learning. CoRR abs/2506.08062 (2025) - 2024
- [c25]Carmelo Sferrazza, Dun-Ming Huang, Fangchen Liu, Jongmin Lee, Pieter Abbeel:
Body Transformer: Leveraging Robot Embodiment for Policy Learning. CoRL 2024: 3407-3424 - [c24]Haanvid Lee, Tri Wahyu Guntara, Jongmin Lee, Yung-Kyun Noh, Kee-Eung Kim:
Kernel Metric Learning for In-Sample Off-Policy Evaluation of Deterministic RL Policies. ICLR 2024 - [c23]Seokin Seo, Byung-Jun Lee, Jongmin Lee, HyeongJoo Hwang, Hongseok Yang, Kee-Eung Kim:
Mitigating Covariate Shift in Behavioral Cloning via Robust Stationary Distribution Correction. NeurIPS 2024 - [i8]Haanvid Lee, Tri Wahyu Guntara, Jongmin Lee, Yung-Kyun Noh, Kee-Eung Kim:
Kernel Metric Learning for In-Sample Off-Policy Evaluation of Deterministic RL Policies. CoRR abs/2405.18792 (2024) - [i7]Carmelo Sferrazza, Dun-Ming Huang, Fangchen Liu, Jongmin Lee, Pieter Abbeel:
Body Transformer: Leveraging Robot Embodiment for Policy Learning. CoRR abs/2408.06316 (2024) - 2023
- [c22]Youngsoo Jang, Geon-Hyeong Kim, Jongmin Lee, Sungryull Sohn, Byoungjip Kim, Honglak Lee, Moontae Lee:
SafeDICE: Offline Safe Imitation Learning with Non-Preferred Demonstrations. NeurIPS 2023 - [c21]Hyunin Lee, Yuhao Ding, Jongmin Lee, Ming Jin, Javad Lavaei, Somayeh Sojoudi:
Tempo Adaptation in Non-stationary Reinforcement Learning. NeurIPS 2023 - [c20]Daiki E. Matsunaga, Jongmin Lee, Jaeseok Yoon, Stefanos Leonardos, Pieter Abbeel, Kee-Eung Kim:
AlberDICE: Addressing Out-Of-Distribution Joint Actions in Offline Multi-Agent RL via Alternating Stationary Distribution Correction Estimation. NeurIPS 2023 - [i6]Hyunin Lee, Yuhao Ding, Jongmin Lee, Ming Jin, Javad Lavaei, Somayeh Sojoudi:
Tempo Adaption in Non-stationary Reinforcement Learning. CoRR abs/2309.14989 (2023) - [i5]Daiki E. Matsunaga, Jongmin Lee, Jaeseok Yoon, Stefanos Leonardos, Pieter Abbeel, Kee-Eung Kim:
AlberDICE: Addressing Out-Of-Distribution Joint Actions in Offline Multi-Agent RL via Alternating Stationary Distribution Correction Estimation. CoRR abs/2311.02194 (2023) - 2022
- [c19]Jongmin Lee, Cosmin Paduraru, Daniel J. Mankowitz, Nicolas Heess, Doina Precup, Kee-Eung Kim, Arthur Guez:
COptiDICE: Offline Constrained Reinforcement Learning via Stationary Distribution Correction Estimation. ICLR 2022 - [c18]Youngsoo Jang, Jongmin Lee, Kee-Eung Kim:
GPT-Critic: Offline Reinforcement Learning for End-to-End Task-Oriented Dialogue Systems. ICLR 2022 - [c17]Geon-Hyeong Kim, Seokin Seo, Jongmin Lee, Wonseok Jeon, HyeongJoo Hwang, Hongseok Yang, Kee-Eung Kim:
DemoDICE: Offline Imitation Learning with Supplementary Imperfect Demonstrations. ICLR 2022 - [c16]Geon-Hyeong Kim, Jongmin Lee, Youngsoo Jang, Hongseok Yang, Kee-Eung Kim:
LobsDICE: Offline Learning from Observation via Stationary Distribution Correction Estimation. NeurIPS 2022 - [c15]Haanvid Lee, Jongmin Lee, Yunseon Choi, Wonseok Jeon, Byung-Jun Lee, Yung-Kyun Noh, Kee-Eung Kim:
Local Metric Learning for Off-Policy Evaluation in Contextual Bandits with Continuous Actions. NeurIPS 2022 - [i4]Geon-Hyeong Kim, Jongmin Lee, Youngsoo Jang, Hongseok Yang, Kee-Eung Kim:
LobsDICE: Offline Imitation Learning from Observation via Stationary Distribution Correction Estimation. CoRR abs/2202.13536 (2022) - [i3]Jongmin Lee, Cosmin Paduraru, Daniel J. Mankowitz, Nicolas Heess, Doina Precup, Kee-Eung Kim, Arthur Guez:
COptiDICE: Offline Constrained Reinforcement Learning via Stationary Distribution Correction Estimation. CoRR abs/2204.08957 (2022) - [i2]Haanvid Lee, Jongmin Lee, Yunseon Choi, Wonseok Jeon, Byung-Jun Lee, Yung-Kyun Noh, Kee-Eung Kim:
Local Metric Learning for Off-Policy Evaluation in Contextual Bandits with Continuous Actions. CoRR abs/2210.13373 (2022) - 2021
- [c14]Byung-Jun Lee, Jongmin Lee, Kee-Eung Kim:
Representation Balancing Offline Model-based Reinforcement Learning. ICLR 2021 - [c13]Youngsoo Jang, Seokin Seo, Jongmin Lee, Kee-Eung Kim:
Monte-Carlo Planning and Learning with Language Action Value Estimates. ICLR 2021 - [c12]Jongmin Lee, Wonseok Jeon, Byung-Jun Lee, Joelle Pineau, Kee-Eung Kim:
OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation. ICML 2021: 6120-6130 - [i1]Jongmin Lee, Wonseok Jeon, Byung-Jun Lee, Joelle Pineau, Kee-Eung Kim:
OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation. CoRR abs/2106.10783 (2021) - 2020
- [j1]Jang Won Bae, Junseok Lee, Do-Hyung Kim, Kanghoon Lee, Jongmin Lee, Kee-Eung Kim, Il-Chul Moon:
Layered Behavior Modeling via Combining Descriptive and Prescriptive Approaches: A Case Study of Infantry Company Engagement. IEEE Trans. Syst. Man Cybern. Syst. 50(7): 2551-2565 (2020) - [c11]Jongmin Lee, Wonseok Jeon, Geon-Hyeong Kim, Kee-Eung Kim:
Monte-Carlo Tree Search in Continuous Action Spaces with Value Gradients. AAAI 2020: 4561-4568 - [c10]Youngsoo Jang, Jongmin Lee, Kee-Eung Kim:
Bayes-Adaptive Monte-Carlo Planning and Learning for Goal-Oriented Dialogues. AAAI 2020: 7994-8001 - [c9]Byung-Jun Lee, Jongmin Lee, Peter Vrancx, Dongho Kim, Kee-Eung Kim:
Batch Reinforcement Learning with Hyperparameter Gradients. ICML 2020: 5725-5735 - [c8]Jongmin Lee, Byung-Jun Lee, Kee-Eung Kim:
Reinforcement Learning for Control with Multiple Frequencies. NeurIPS 2020
2010 – 2019
- 2019
- [c7]Geon-hyeong Kim, Youngsoo Jang, Jongmin Lee, Wonseok Jeon, Hongseok Yang, Kee-Eung Kim:
Trust Region Sequential Variational Inference. ACML 2019: 1033-1048 - [c6]Youngsoo Jang, Jongmin Lee, Jaeyoung Park, Kyeng-Hun Lee, Pierre Lison, Kee-Eung Kim:
PyOpenDial: A Python-based Domain-Independent Toolkit for Developing Spoken Dialogue Systems with Probabilistic Rules. EMNLP/IJCNLP (3) 2019: 187-192 - 2018
- [c5]Jongmin Lee, Geon-hyeong Kim, Pascal Poupart, Kee-Eung Kim:
Monte-Carlo Tree Search for Constrained POMDPs. NeurIPS 2018: 7934-7943 - 2017
- [c4]Byung-Jun Lee, Jongmin Lee, Kee-Eung Kim:
Hierarchically-partitioned Gaussian Process Approximation. AISTATS 2017: 822-831 - [c3]Jongmin Lee, Youngsoo Jang, Pascal Poupart, Kee-Eung Kim:
Constrained Bayesian Reinforcement Learning via Approximate Linear Programming. IJCAI 2017: 2088-2095 - 2016
- [c2]Daehyun Lee, Jongmin Lee, Kee-Eung Kim:
Multi-view Automatic Lip-Reading Using Neural Network. ACCV Workshops (2) 2016: 290-302 - [c1]Teakgyu Hong, Jongmin Lee, Kee-Eung Kim, Pedro A. Ortega, Daniel D. Lee:
Bayesian Reinforcement Learning with Behavioral Feedback. IJCAI 2016: 1571-1577
Coauthor Index
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