Lee, Jongmin

44 publications

TMLR 2025 Deflated Dynamics Value Iteration Jongmin Lee, Amin Rakhsha, Ernest K. Ryu, Amir-massoud Farahmand

CVPR 2025 Dense-SfM: Structure from Motion with Dense Consistent Matching JongMin Lee, Sungjoo Yoo

NeurIPS 2025 FairDICE: Fairness-Driven Offline Multi-Objective Reinforcement Learning Woosung Kim, Jinho Lee, Jongmin Lee, Byung-Jun Lee

NeurIPS 2025 Finite-Time Bounds for Average-Reward Fitted Q-Iteration Jongmin Lee, Ernest K. Ryu

ICML 2025 Near-Optimal Sample Complexity for MDPs via Anchoring Jongmin Lee, Mario Bravo, Roberto Cominetti

ICLR 2025 Optimal Non-Asymptotic Rates of Value Iteration for Average-Reward Markov Decision Processes Jongmin Lee, Ernest K. Ryu

ICLR 2025 SEMDICE: Off-Policy State Entropy Maximization via Stationary Distribution Correction Estimation Jongmin Lee, Meiqi Sun, Pieter Abbeel

NeurIPS 2024 3D Equivariant Pose Regression via Direct Wigner-D Harmonics Prediction Jongmin Lee, Minsu Cho

CoRL 2024 Body Transformer: Leveraging Robot Embodiment for Policy Learning Carmelo Sferrazza, Dun-Ming Huang, Fangchen Liu, Jongmin Lee, Pieter Abbeel

ICLR 2024 Kernel Metric Learning for In-Sample Off-Policy Evaluation of Deterministic RL Policies Haanvid Lee, Tri Wahyu Guntara, Jongmin Lee, Yung-Kyun Noh, Kee-Eung Kim

AAAI 2024 MFOS: Model-Free & One-Shot Object Pose Estimation JongMin Lee, Yohann Cabon, Romain Brégier, Sungjoo Yoo, Jérôme Revaud

NeurIPS 2024 Mitigating Covariate Shift in Behavioral Cloning via Robust Stationary Distribution Correction Seokin Seo, Byung-Jun Lee, Jongmin Lee, HyeongJoo Hwang, Hongseok Yang, Kee-Eung Kim

IJCAI 2024 Motion-Aware Heatmap Regression for Human Pose Estimation in Videos Inpyo Song, Jongmin Lee, Moonwook Ryu, Jangwon Lee

NeurIPS 2024 ROIDICE: Offline Return on Investment Maximization for Efficient Decision Making Woosung Kim, Hayeong Lee, Jongmin Lee, Byung-Jun Lee

CVPRW 2024 SACReg: Scene-Agnostic Coordinate Regression for Visual Localization Jérôme Revaud, Yohann Cabon, Romain Brégier, JongMin Lee, Philippe Weinzaepfel

NeurIPS 2023 Accelerating Value Iteration with Anchoring Jongmin Lee, Ernest Ryu

NeurIPS 2023 AlberDICE: Addressing Out-of-Distribution Joint Actions in Offline Multi-Agent RL via Alternating Stationary Distribution Correction Estimation Daiki E. Matsunaga, Jongmin Lee, Jaeseok Yoon, Stefanos Leonardos, Pieter Abbeel, Kee-Eung Kim

CVPR 2023 Learning Rotation-Equivariant Features for Visual Correspondence Jongmin Lee, Byungjin Kim, Seungwook Kim, Minsu Cho

CVPRW 2023 Multi-Scale Local Implicit Keypoint Descriptor for Keypoint Matching JongMin Lee, Eunhyeok Park, Sungjoo Yoo

NeurIPS 2023 SafeDICE: Offline Safe Imitation Learning with Non-Preferred Demonstrations Youngsoo Jang, Geon-Hyeong Kim, Jongmin Lee, Sungryull Sohn, Byoungjip Kim, Honglak Lee, Moontae Lee

NeurIPS 2023 Tempo Adaptation in Non-Stationary Reinforcement Learning Hyunin Lee, Yuhao Ding, Jongmin Lee, Ming Jin, Javad Lavaei, Somayeh Sojoudi

ICLR 2022 COptiDICE: Offline Constrained Reinforcement Learning via Stationary Distribution Correction Estimation Jongmin Lee, Cosmin Paduraru, Daniel J Mankowitz, Nicolas Heess, Doina Precup, Kee-Eung Kim, Arthur Guez

ICLR 2022 DemoDICE: Offline Imitation Learning with Supplementary Imperfect Demonstrations Geon-Hyeong Kim, Seokin Seo, Jongmin Lee, Wonseok Jeon, HyeongJoo Hwang, Hongseok Yang, Kee-Eung Kim

ICLR 2022 GPT-Critic: Offline Reinforcement Learning for End-to-End Task-Oriented Dialogue Systems Youngsoo Jang, Jongmin Lee, Kee-Eung Kim

NeurIPS 2022 LobsDICE: Offline Learning from Observation via Stationary Distribution Correction Estimation Geon-Hyeong Kim, Jongmin Lee, Youngsoo Jang, Hongseok Yang, Kee-Eung Kim

NeurIPS 2022 Local Metric Learning for Off-Policy Evaluation in Contextual Bandits with Continuous Actions Haanvid Lee, Jongmin Lee, Yunseon Choi, Wonseok Jeon, Byung-Jun Lee, Yung-Kyun Noh, Kee-Eung Kim

ICML 2022 Neural Tangent Kernel Analysis of Deep Narrow Neural Networks Jongmin Lee, Joo Young Choi, Ernest K Ryu, Albert No

CVPR 2022 Self-Supervised Equivariant Learning for Oriented Keypoint Detection Jongmin Lee, Byungjin Kim, Minsu Cho

NeurIPS 2021 A Geometric Structure of Acceleration and Its Role in Making Gradients Small Fast Jongmin Lee, Chanwoo Park, Ernest Ryu

WACV 2021 Learning to Distill Convolutional Features into Compact Local Descriptors Jongmin Lee, Yoonwoo Jeong, Seungwook Kim, Juhong Min, Minsu Cho

ICLR 2021 Monte-Carlo Planning and Learning with Language Action Value Estimates Youngsoo Jang, Seokin Seo, Jongmin Lee, Kee-Eung Kim

ICML 2021 OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation Jongmin Lee, Wonseok Jeon, Byungjun Lee, Joelle Pineau, Kee-Eung Kim

ICLR 2021 Representation Balancing Offline Model-Based Reinforcement Learning Byung-Jun Lee, Jongmin Lee, Kee-Eung Kim

ICML 2020 Batch Reinforcement Learning with Hyperparameter Gradients Byungjun Lee, Jongmin Lee, Peter Vrancx, Dongho Kim, Kee-Eung Kim

AAAI 2020 Bayes-Adaptive Monte-Carlo Planning and Learning for Goal-Oriented Dialogues Youngsoo Jang, Jongmin Lee, Kee-Eung Kim

ECCV 2020 Learning to Compose Hypercolumns for Visual Correspondence Juhong Min, Jongmin Lee, Jean Ponce, Minsu Cho

AAAI 2020 Monte-Carlo Tree Search in Continuous Action Spaces with Value Gradients Jongmin Lee, Wonseok Jeon, Geon-Hyeong Kim, Kee-Eung Kim

NeurIPS 2020 Reinforcement Learning for Control with Multiple Frequencies Jongmin Lee, Byung-Jun Lee, Kee-Eung Kim

ACML 2019 Trust Region Sequential Variational Inference Geon-Hyeong Kim, Youngsoo Jang, Jongmin Lee, Wonseok Jeon, Hongseok Yang, Kee-Eung Kim

ECCV 2018 Attentive Semantic Alignment with Offset-Aware Correlation Kernels Paul Hongsuck Seo, Jongmin Lee, Deunsol Jung, Bohyung Han, Minsu Cho

NeurIPS 2018 Monte-Carlo Tree Search for Constrained POMDPs Jongmin Lee, Geon-hyeong Kim, Pascal Poupart, Kee-Eung Kim

IJCAI 2017 Constrained Bayesian Reinforcement Learning via Approximate Linear Programming Jongmin Lee, Youngsoo Jang, Pascal Poupart, Kee-Eung Kim

AISTATS 2017 Hierarchically-Partitioned Gaussian Process Approximation Byung-Jun Lee, Jongmin Lee, Kee-Eung Kim

IJCAI 2016 Bayesian Reinforcement Learning with Behavioral Feedback Teakgyu Hong, Jongmin Lee, Kee-Eung Kim, Pedro A. Ortega, Daniel D. Lee