Jongmin Lee

38 papers A* 21A 1C 1Misc 1Journal 12Unranked 2
YearRankTypeTitle / Venue / Authors
2025 J jnl
FairDICE: Fairness-Driven Offline Multi-Objective Reinforcement Learning.
CoRR
Woosung Kim, Jinho Lee, Jongmin Lee, Byung-Jun Lee
2025 A* conf
SEMDICE: Off-policy State Entropy Maximization via Stationary Distribution Correction Estimation.
ICLR
Jongmin Lee, Meiqi Sun, Pieter Abbeel
2025 J jnl
SEMDICE: Off-policy State Entropy Maximization via Stationary Distribution Correction Estimation.
CoRR
Jongmin Lee, Meiqi Sun, Pieter Abbeel
2025 J jnl
Semi-gradient DICE for Offline Constrained Reinforcement Learning.
CoRR
Woosung Kim, JunHo Seo, Jongmin Lee, Byung-Jun Lee
2024 Misc conf
Body Transformer: Leveraging Robot Embodiment for Policy Learning.
CoRL
Carmelo Sferrazza, Dun-Ming Huang, Fangchen Liu, Jongmin Lee, Pieter Abbeel
2024 J jnl
Body Transformer: Leveraging Robot Embodiment for Policy Learning.
CoRR
Carmelo Sferrazza, Dun-Ming Huang, Fangchen Liu, Jongmin Lee, Pieter Abbeel
2024 A* conf
Kernel Metric Learning for In-Sample Off-Policy Evaluation of Deterministic RL Policies.
ICLR
Haanvid Lee, Tri Wahyu Guntara, Jongmin Lee, Yung-Kyun Noh, Kee-Eung Kim
2024 J jnl
Kernel Metric Learning for In-Sample Off-Policy Evaluation of Deterministic RL Policies.
CoRR
Haanvid Lee, Tri Wahyu Guntara, Jongmin Lee, Yung-Kyun Noh, Kee-Eung Kim
2024 A* conf
Mitigating Covariate Shift in Behavioral Cloning via Robust Stationary Distribution Correction.
NeurIPS
Seokin Seo, Byung-Jun Lee, Jongmin Lee, HyeongJoo Hwang, Hongseok Yang, Kee-Eung Kim
2023 A* conf
AlberDICE: Addressing Out-Of-Distribution Joint Actions in Offline Multi-Agent RL via Alternating Stationary Distribution Correction Estimation.
NeurIPS
Daiki E. Matsunaga, Jongmin Lee, Jaeseok Yoon, Stefanos Leonardos, Pieter Abbeel, Kee-Eung Kim
2023 J jnl
AlberDICE: Addressing Out-Of-Distribution Joint Actions in Offline Multi-Agent RL via Alternating Stationary Distribution Correction Estimation.
CoRR
Daiki E. Matsunaga, Jongmin Lee, Jaeseok Yoon, Stefanos Leonardos, Pieter Abbeel, Kee-Eung Kim
2023 A* conf
SafeDICE: Offline Safe Imitation Learning with Non-Preferred Demonstrations.
NeurIPS
Youngsoo Jang, Geon-Hyeong Kim, Jongmin Lee, Sungryull Sohn, Byoungjip Kim, Honglak Lee, Moontae Lee
2023 A* conf
Tempo Adaptation in Non-stationary Reinforcement Learning.
NeurIPS
Hyunin Lee, Yuhao Ding, Jongmin Lee, Ming Jin, Javad Lavaei, Somayeh Sojoudi
2023 J jnl
Tempo Adaption in Non-stationary Reinforcement Learning.
CoRR
Hyunin Lee, Yuhao Ding, Jongmin Lee, Ming Jin, Javad Lavaei, Somayeh Sojoudi
2022 A* conf
COptiDICE: Offline Constrained Reinforcement Learning via Stationary Distribution Correction Estimation.
ICLR
Jongmin Lee, Cosmin Paduraru, Daniel J. Mankowitz, Nicolas Heess, Doina Precup, Kee-Eung Kim, Arthur Guez
2022 J jnl
COptiDICE: Offline Constrained Reinforcement Learning via Stationary Distribution Correction Estimation.
CoRR
Jongmin Lee, Cosmin Paduraru, Daniel J. Mankowitz, Nicolas Heess, Doina Precup, Kee-Eung Kim, Arthur Guez
2022 A* conf
DemoDICE: Offline Imitation Learning with Supplementary Imperfect Demonstrations.
ICLR
Geon-Hyeong Kim, Seokin Seo, Jongmin Lee, Wonseok Jeon, HyeongJoo Hwang, Hongseok Yang, Kee-Eung Kim
2022 A* conf
GPT-Critic: Offline Reinforcement Learning for End-to-End Task-Oriented Dialogue Systems.
ICLR
Youngsoo Jang, Jongmin Lee, Kee-Eung Kim
2022 J jnl
LobsDICE: Offline Imitation Learning from Observation via Stationary Distribution Correction Estimation.
CoRR
Geon-Hyeong Kim, Jongmin Lee, Youngsoo Jang, Hongseok Yang, Kee-Eung Kim
2022 A* conf
LobsDICE: Offline Learning from Observation via Stationary Distribution Correction Estimation.
NeurIPS
Geon-Hyeong Kim, Jongmin Lee, Youngsoo Jang, Hongseok Yang, Kee-Eung Kim
2022 A* conf
Local Metric Learning for Off-Policy Evaluation in Contextual Bandits with Continuous Actions.
NeurIPS
Haanvid Lee, Jongmin Lee, Yunseon Choi, Wonseok Jeon, Byung-Jun Lee, Yung-Kyun Noh, Kee-Eung Kim
2022 J jnl
Local Metric Learning for Off-Policy Evaluation in Contextual Bandits with Continuous Actions.
CoRR
Haanvid Lee, Jongmin Lee, Yunseon Choi, Wonseok Jeon, Byung-Jun Lee, Yung-Kyun Noh, Kee-Eung Kim
2021 A* conf
Monte-Carlo Planning and Learning with Language Action Value Estimates.
ICLR
Youngsoo Jang, Seokin Seo, Jongmin Lee, Kee-Eung Kim
2021 A* conf
OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation.
ICML
Jongmin Lee, Wonseok Jeon, Byung-Jun Lee, Joelle Pineau, Kee-Eung Kim
2021 J jnl
OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation.
CoRR
Jongmin Lee, Wonseok Jeon, Byung-Jun Lee, Joelle Pineau, Kee-Eung Kim
2021 A* conf
Representation Balancing Offline Model-based Reinforcement Learning.
ICLR
Byung-Jun Lee, Jongmin Lee, Kee-Eung Kim
2020 A* conf
Batch Reinforcement Learning with Hyperparameter Gradients.
ICML
Byung-Jun Lee, Jongmin Lee, Peter Vrancx, Dongho Kim, Kee-Eung Kim
2020 A* conf
Bayes-Adaptive Monte-Carlo Planning and Learning for Goal-Oriented Dialogues.
AAAI
Youngsoo Jang, Jongmin Lee, Kee-Eung Kim
2020 J jnl
Layered Behavior Modeling via Combining Descriptive and Prescriptive Approaches: A Case Study of Infantry Company Engagement.
IEEE Trans. Syst. Man Cybern. Syst.
Jang Won Bae, Junseok Lee, Do-Hyung Kim, Kanghoon Lee, Jongmin Lee, Kee-Eung Kim, Il-Chul Moon
2020 A* conf
Monte-Carlo Tree Search in Continuous Action Spaces with Value Gradients.
AAAI
Jongmin Lee, Wonseok Jeon, Geon-Hyeong Kim, Kee-Eung Kim
2020 A* conf
Reinforcement Learning for Control with Multiple Frequencies.
NeurIPS
Jongmin Lee, Byung-Jun Lee, Kee-Eung Kim
2019 — conf
PyOpenDial: A Python-based Domain-Independent Toolkit for Developing Spoken Dialogue Systems with Probabilistic Rules.
EMNLP/IJCNLP (3)
Youngsoo Jang, Jongmin Lee, Jaeyoung Park, Kyeng-Hun Lee, Pierre Lison, Kee-Eung Kim
2019 C conf
Trust Region Sequential Variational Inference.
ACML
Geon-Hyeong Kim, Youngsoo Jang, Jongmin Lee, Wonseok Jeon, Hongseok Yang, Kee-Eung Kim
2018 A* conf
Monte-Carlo Tree Search for Constrained POMDPs.
NeurIPS
Jongmin Lee, Geon-Hyeong Kim, Pascal Poupart, Kee-Eung Kim
2017 A* conf
Constrained Bayesian Reinforcement Learning via Approximate Linear Programming.
IJCAI
Jongmin Lee, Youngsoo Jang, Pascal Poupart, Kee-Eung Kim
2017 A conf
Hierarchically-partitioned Gaussian Process Approximation.
AISTATS
Byung-Jun Lee, Jongmin Lee, Kee-Eung Kim
2016 A* conf
Bayesian Reinforcement Learning with Behavioral Feedback.
IJCAI
Teakgyu Hong, Jongmin Lee, Kee-Eung Kim, Pedro A. Ortega, Daniel D. Lee
2016 — conf
Multi-view Automatic Lip-Reading Using Neural Network.
ACCV Workshops (2)
Daehyun Lee, Jongmin Lee, Kee-Eung Kim