| 2026 | AAAI | Optimizing Preferential Rate in Retail Lending with Causal Inference and Domain Adaptation. | Jimyung Choi, Yujin Lee, Hyeryeong Oh, Sumin Shin, Jaehyun Kim, Wooyoung Kim, Kee-Eung Kim |
| 2025 | ICLR | Monet: Mixture of Monosemantic Experts for Transformers. | Jungwoo Park, Ahn Young Jin, Kee-Eung Kim, Jaewoo Kang |
| 2025 | NAACL | Goal-Conditioned DPO: Prioritizing Safety in Misaligned Instructions. | Joo Bon Maeng, Seongmin Lee, Seokin Seo, Kee-Eung Kim |
| 2024 | AAAI | Stitching Sub-trajectories with Conditional Diffusion Model for Goal-Conditioned Offline RL. | Sungyoon Kim, Yunseon Choi, Daiki E. Matsunaga, Kee-Eung Kim |
| 2024 | AAAI | A Submodular Optimization Approach to Accountable Loan Approval. | Kyungsik Lee, Hana Yoo, Sumin Shin, Wooyoung Kim, Yeonung Baek, Hyunjin Kang, Jaehyun Kim, Kee-Eung Kim |
| 2024 | ACL | Hard Prompts Made Interpretable: Sparse Entropy Regularization for Prompt Tuning with RL. | Yunseon Choi, Sangmin Bae, Seonghyun Ban, Minchan Jeong, Chuheng Zhang, Lei Song, Li Zhao, Jiang Bian, Kee-Eung Kim |
| 2024 | EMNLP | GDPO: Learning to Directly Align Language Models with Diversity Using GFlowNets. | Oh Joon Kwon, Daiki E. Matsunaga, Kee-Eung Kim |
| 2024 | ICLR | 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 |
| 2024 | IJCAI | Diversification of Adaptive Policy for Effective Offline Reinforcement Learning. | Yunseon Choi, Li Zhao, Chuheng Zhang, Lei Song, Jiang Bian, Kee-Eung Kim |
| 2024 | Interspeech | SyncVSR: Data-Efficient Visual Speech Recognition with End-to-End Crossmodal Audio Token Synchronization. | Youngjin Ahn, Jungwoo Park, Sangha Park, Jonghyun Choi, Kee-Eung Kim |
| 2023 | AAAI | Trustworthy Residual Vehicle Value Prediction for Auto Finance. | Mihye Kim, Jimyung Choi, Jaehyun Kim, Wooyoung Kim, Yeonung Baek, Gisuk Bang, Kwangwoon Son, Yeonman Ryou, Kee-Eung Kim |
| 2023 | EMNLP | Bayesian Multi-Task Transfer Learning for Soft Prompt Tuning. | Haeju Lee, Minchan Jeong, Se-Young Yun, Kee-Eung Kim |
| 2023 | ICML | Information-Theoretic State Space Model for Multi-View Reinforcement Learning. | HyeongJoo Hwang, Seokin Seo, Youngsoo Jang, Sungyoon Kim, Geon-Hyeong Kim, Seunghoon Hong, Kee-Eung Kim |
| 2022 | ICLR | 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 |
| 2022 | ICLR | Structure-Aware Transformer Policy for Inhomogeneous Multi-Task Reinforcement Learning. | Sunghoon Hong, Deunsol Yoon, Kee-Eung Kim |
| 2022 | ICLR | GPT-Critic: Offline Reinforcement Learning for End-to-End Task-Oriented Dialogue Systems. | Youngsoo Jang, Jongmin Lee, Kee-Eung Kim |
| 2022 | ICLR | DemoDICE: Offline Imitation Learning with Supplementary Imperfect Demonstrations. | Geon-Hyeong Kim, Seokin Seo, Jongmin Lee, Wonseok Jeon, HyeongJoo Hwang, Hongseok Yang, Kee-Eung Kim |
| 2022 | ICML | PAC-Net: A Model Pruning Approach to Inductive Transfer Learning. | Sanghoon Myung, In Huh, Wonik Jang, Jae Myung Choe, Jisu Ryu, Daesin Kim, Kee-Eung Kim, Changwook Jeong |
| 2022 | IJCAI | Data Augmentation for Learning to Play in Text-Based Games. | Jinhyeon Kim, Kee-Eung Kim |
| 2022 | NAACL | Learning to Embed Multi-Modal Contexts for Situated Conversational Agents. | Haeju Lee, Oh Joon Kwon, Yunseon Choi, Minho Park, Ran Han, Yoonhyung Kim, Jinhyeon Kim, Youngjune Lee, Haebin Shin, Kangwook Lee, Kee-Eung Kim |
| 2021 | CIKM | Dual Correction Strategy for Ranking Distillation in Top-N Recommender System. | Youngjune Lee, Kee-Eung Kim |
| 2021 | ICIS | Personalized Treatment Using Biologics: An Analysis Using Counterfactual Regression Based on Deep Learning. | Seongho Eun, Bon San Koo, Ji Seon Oh, Kee-Eung Kim, Byungtae Lee |
| 2021 | ICLR | Representation Balancing Offline Model-based Reinforcement Learning. | Byung-Jun Lee, Jongmin Lee, Kee-Eung Kim |
| 2021 | ICLR | Monte-Carlo Planning and Learning with Language Action Value Estimates. | Youngsoo Jang, Seokin Seo, Jongmin Lee, Kee-Eung Kim |
| 2021 | ICLR | Winning the L2RPN Challenge: Power Grid Management via Semi-Markov Afterstate Actor-Critic. | Deunsol Yoon, Sunghoon Hong, Byung-Jun Lee, Kee-Eung Kim |
| 2021 | ICML | OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation. | Jongmin Lee, Wonseok Jeon, Byung-Jun Lee, Joelle Pineau, Kee-Eung Kim |
| 2020 | AAAI | Bayes-Adaptive Monte-Carlo Planning and Learning for Goal-Oriented Dialogues. | Youngsoo Jang, Jongmin Lee, Kee-Eung Kim |
| 2020 | AAAI | Residual Neural Processes. | Byung-Jun Lee, Seunghoon Hong, Kee-Eung Kim |
| 2020 | AAAI | Monte-Carlo Tree Search in Continuous Action Spaces with Value Gradients. | Jongmin Lee, Wonseok Jeon, Geon-Hyeong Kim, Kee-Eung Kim |
| 2020 | ACL | End-to-End Neural Pipeline for Goal-Oriented Dialogue Systems using GPT-2. | DongHoon Ham, Jeong-Gwan Lee, Youngsoo Jang, Kee-Eung Kim |
| 2020 | ICML | Variational Inference for Sequential Data with Future Likelihood Estimates. | Geon-Hyeong Kim, Youngsoo Jang, Hongseok Yang, Kee-Eung Kim |
| 2020 | ICML | Batch Reinforcement Learning with Hyperparameter Gradients. | Byung-Jun Lee, Jongmin Lee, Peter Vrancx, Dongho Kim, Kee-Eung Kim |
| 2019 | ACML | Trust Region Sequential Variational Inference. | Geon-hyeong Kim, Youngsoo Jang, Jongmin Lee, Wonseok Jeon, Hongseok Yang, Kee-Eung Kim |
| 2019 | EMNLP | PyOpenDial: A Python-based Domain-Independent Toolkit for Developing Spoken Dialogue Systems with Probabilistic Rules. | Youngsoo Jang, Jongmin Lee, Jaeyoung Park, Kyeng-Hun Lee, Pierre Lison, Kee-Eung Kim |
| 2018 | AAAI | Imitation Learning via Kernel Mean Embedding. | Kee-Eung Kim, Hyun Soo Park |
| 2017 | AISTATS | Hierarchically-partitioned Gaussian Process Approximation. | Byung-Jun Lee, Jongmin Lee, Kee-Eung Kim |
| 2017 | IJCAI | Constrained Bayesian Reinforcement Learning via Approximate Linear Programming. | Jongmin Lee, Youngsoo Jang, Pascal Poupart, Kee-Eung Kim |
| 2017 | SMC | Hybrid modeling and simulation of tactical maneuvers in computer generated force. | Jang Won Bae, Bowon Nam, Kee-Eung Kim, Junseok Lee, Il-Chul Moon |
| 2016 | ACCV | Multi-view Automatic Lip-Reading Using Neural Network. | Daehyun Lee, Jongmin Lee, Kee-Eung Kim |
| 2016 | IJCAI | Bayesian Reinforcement Learning with Behavioral Feedback. | Teakgyu Hong, Jongmin Lee, Kee-Eung Kim, Pedro A. Ortega, Daniel D. Lee |
| 2015 | AAAI | Reward Shaping for Model-Based Bayesian Reinforcement Learning. | Hyeoneun Kim, Woosang Lim, Kanghoon Lee, Yung-Kyun Noh, Kee-Eung Kim |
| 2015 | AAAI | Tighter Value Function Bounds for Bayesian Reinforcement Learning. | Kanghoon Lee, Kee-Eung Kim |
| 2015 | AAAI | Approximate Linear Programming for Constrained Partially Observable Markov Decision Processes. | Pascal Poupart, Aarti Malhotra, Pei Pei, Kee-Eung Kim, Bongseok Goh, Michael Bowling |
| 2015 | AISTATS | Reactive bandits with attitude. | Pedro A. Ortega, Kee-Eung Kim, Daniel D. Lee |
| 2014 | SIGdial | Optimizing Generative Dialog State Tracker via Cascading Gradient Descent. | Byung-Jun Lee, Woosang Lim, Daejoong Kim, Kee-Eung Kim |
| 2013 | IJCAI | Bayesian Nonparametric Feature Construction for Inverse Reinforcement Learning. | Jaedeug Choi, Kee-Eung Kim |
| 2013 | SIGdial | Engineering Statistical Dialog State Trackers: A Case Study on DSTC. | Daejoong Kim, Jaedeug Choi, Kee-Eung Kim, Jungsu Lee, Jinho Sohn |
| 2011 | AAAI | A POMDP-Based Optimal Control of P300-Based Brain-Computer Interfaces. | Jaeyoung Park, Kee-Eung Kim, Yoon-Kyu Song |
| 2011 | IJCAI | Point-Based Value Iteration for Constrained POMDPs. | Dongho Kim, Jaesong Lee, Kee-Eung Kim, Pascal Poupart |
| 2011 | UAI | A Geometric Traversal Algorithm for Reward-Uncertain MDPs. | Eunsoo Oh, Kee-Eung Kim |
| 2010 | IUI | A POMDP approach to P300-based brain-computer interfaces. | Jaeyoung Park, Kee-Eung Kim, Sungho Jo |
| 2010 | PRICAI | Point-Based Bounded Policy Iteration for Decentralized POMDPs. | Youngwook Kim, Kee-Eung Kim |
| 2009 | IJCAI | Inverse Reinforcement Learning in Partially Observable Environments. | Jaedeug Choi, Kee-Eung Kim |
| 2008 | AAAI | Exploiting Symmetries in POMDPs for Point-Based Algorithms. | Kee-Eung Kim |
| 2008 | AAAI | Symbolic Heuristic Search Value Iteration for Factored POMDPs. | Hyeong Seop Sim, Kee-Eung Kim, Jin Hyung Kim, Du-Seong Chang, Myoung-Wan Koo |
| 2008 | Interspeech | Effects of user modeling on POMDP-based dialogue systems. | Dongho Kim, Hyeong Seop Sim, Kee-Eung Kim, Jin Hyung Kim, Hyunjeong Kim, Joo Won Sung |
| 2006 | AAAI | Hand Grip Pattern Recognition for Mobile User Interfaces. | Kee-Eung Kim, Wook Chang, Sung-Jung Cho, Junghyun Shim, Hyunjeong Lee, Joonah Park, Youngbeom Lee, Sangryoung Kim |
| 2002 | PRICAI | Solving Factored MDPs with Large Action Space Using Algebraic Decision Diagrams. | Kee-Eung Kim, Thomas L. Dean |
| 2001 | IJCAI | Solving Factored MDPs via Non-Homogeneous Partitioning. | Kee-Eung Kim, Thomas L. Dean |
| 2000 | UAI | Learning to Cooperate via Policy Search. | Leonid Peshkin, Kee-Eung Kim, Nicolas Meuleau, Leslie Pack Kaelbling |
| 1999 | UAI | Solving POMDPs by Searching the Space of Finite Policies. | Nicolas Meuleau, Kee-Eung Kim, Leslie Pack Kaelbling, Anthony R. Cassandra |
| 1999 | UAI | Learning Finite-State Controllers for Partially Observable Environments. | Nicolas Meuleau, Leonid Peshkin, Kee-Eung Kim, Leslie Pack Kaelbling |
| 1998 | AAAI | Solving Very Large Weakly Coupled Markov Decision Processes. | Nicolas Meuleau, Milos Hauskrecht, Kee-Eung Kim, Leonid Peshkin, Leslie Pack Kaelbling, Thomas L. Dean, Craig Boutilier |