Jongmin Lee

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 26

Top Topics

Variational Inference

Continuous Action

Monte Carlo Tree Search

Reinforcement Learning

Top Venues

Publications

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 (2024)
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)
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)
Youngsoo Jang, Jongmin Lee, Kee-Eung Kim
GPT-Critic: Offline Reinforcement Learning for End-to-End Task-Oriented Dialogue Systems. ICLR (2022)
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)
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 (2022)
Geon-Hyeong Kim, Jongmin Lee, Youngsoo Jang, Hongseok Yang, Kee-Eung Kim
LobsDICE: Offline Imitation Learning from Observation via Stationary Distribution Correction Estimation. CoRR (2022)
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)
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 (2022)
Geon-Hyeong Kim, Jongmin Lee, Youngsoo Jang, Hongseok Yang, Kee-Eung Kim
LobsDICE: Offline Learning from Observation via Stationary Distribution Correction Estimation. NeurIPS (2022)
Jongmin Lee, Wonseok Jeon, Byung-Jun Lee, Joelle Pineau, Kee-Eung Kim
OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation. CoRR (2021)
Byung-Jun Lee, Jongmin Lee, Kee-Eung Kim
Representation Balancing Offline Model-based Reinforcement Learning. ICLR (2021)
Youngsoo Jang, Seokin Seo, Jongmin Lee, Kee-Eung Kim
Monte-Carlo Planning and Learning with Language Action Value Estimates. ICLR (2021)
Jongmin Lee, Wonseok Jeon, Byung-Jun Lee, Joelle Pineau, Kee-Eung Kim
OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation. ICML (2021)
Jongmin Lee, Byung-Jun Lee, Kee-Eung Kim
Reinforcement Learning for Control with Multiple Frequencies. NeurIPS (2020)
Youngsoo Jang, Jongmin Lee, Kee-Eung Kim
Bayes-Adaptive Monte-Carlo Planning and Learning for Goal-Oriented Dialogues. AAAI (2020)
Byung-Jun Lee, Jongmin Lee, Peter Vrancx, Dongho Kim, Kee-Eung Kim
Batch Reinforcement Learning with Hyperparameter Gradients. ICML (2020)
Jongmin Lee, Wonseok Jeon, Geon-Hyeong Kim, Kee-Eung Kim
Monte-Carlo Tree Search in Continuous Action Spaces with Value Gradients. AAAI (2020)
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) (2020)
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)
Geon-hyeong Kim, Youngsoo Jang, Jongmin Lee, Wonseok Jeon, Hongseok Yang, Kee-Eung Kim
Trust Region Sequential Variational Inference. ACML (2019)
Jongmin Lee, Geon-hyeong Kim, Pascal Poupart, Kee-Eung Kim
Monte-Carlo Tree Search for Constrained POMDPs. NeurIPS (2018)
Byung-Jun Lee, Jongmin Lee, Kee-Eung Kim
Hierarchically-partitioned Gaussian Process Approximation. AISTATS (2017)
Jongmin Lee, Youngsoo Jang, Pascal Poupart, Kee-Eung Kim
Constrained Bayesian Reinforcement Learning via Approximate Linear Programming. IJCAI (2017)
Teakgyu Hong, Jongmin Lee, Kee-Eung Kim, Pedro A. Ortega, Daniel D. Lee
Bayesian Reinforcement Learning with Behavioral Feedback. IJCAI (2016)
Daehyun Lee, Jongmin Lee, Kee-Eung Kim
Multi-view Automatic Lip-Reading Using Neural Network. ACCV Workshops (2) (2016)