Kee-Eung Kim - RankMe

129 papers A* 51A 10B 3C 3Journal 42Unranked 19

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	Optimizing Preferential Rate in Retail Lending with Causal Inference and Domain Adaptation. AAAI Jimyung Choi, Yujin Lee, Hyeryeong Oh, Sumin Shin, Jaehyun Kim, Wooyoung Kim, Kee-Eung Kim
2025	—	`conf`	Goal-Conditioned DPO: Prioritizing Safety in Misaligned Instructions. NAACL (Long Papers) Joo Bon Maeng, Seongmin Lee, Seokin Seo, Kee-Eung Kim
2025	A*	`conf`	Monet: Mixture of Monosemantic Experts for Transformers. ICLR Jungwoo Park, Ahn Young Jin, Kee-Eung Kim, Jaewoo Kang
2024	A*	`conf`	A Submodular Optimization Approach to Accountable Loan Approval. AAAI Kyungsik Lee, Hana Yoo, Sumin Shin, Wooyoung Kim, Yeonung Baek, Hyunjin Kang, Jaehyun Kim, Kee-Eung Kim
2024	J	`jnl`	A submodular optimization approach to trustworthy loan approval automation. AI Mag. Kyungsik Lee, Hana Yoo, Sumin Shin, Wooyoung Kim, Yeonung Baek, Hyunjin Kang, Jaehyun Kim, Kee-Eung Kim
2024	J	`jnl`	Bayesian Multi-Task Transfer Learning for Soft Prompt Tuning. CoRR Haeju Lee, Minchan Jeong, Se-Young Yun, Kee-Eung Kim
2024	A*	`conf`	Data Augmentation with Diffusion for Open-Set Semi-Supervised Learning. NeurIPS Seonghyun Ban, Heesan Kong, Kee-Eung Kim
2024	A*	`conf`	Diversification of Adaptive Policy for Effective Offline Reinforcement Learning. IJCAI Yunseon Choi, Li Zhao, Chuheng Zhang, Lei Song, Jiang Bian, Kee-Eung Kim
2024	A*	`conf`	GDPO: Learning to Directly Align Language Models with Diversity Using GFlowNets. EMNLP Oh Joon Kwon, Daiki E. Matsunaga, Kee-Eung Kim
2024	J	`jnl`	GDPO: Learning to Directly Align Language Models with Diversity Using GFlowNets. CoRR Oh Joon Kwon, Daiki E. Matsunaga, Kee-Eung Kim
2024	—	`conf`	Hard Prompts Made Interpretable: Sparse Entropy Regularization for Prompt Tuning with RL. ACL (1) Yunseon Choi, Sangmin Bae, Seonghyun Ban, Minchan Jeong, Chuheng Zhang, Lei Song, Li Zhao, Jiang Bian, Kee-Eung Kim
2024	J	`jnl`	Hard Prompts Made Interpretable: Sparse Entropy Regularization for Prompt Tuning with RL. CoRR Yunseon Choi, Sangmin Bae, Seonghyun Ban, Minchan Jeong, Chuheng Zhang, Lei Song, Li Zhao, Jiang Bian, Kee-Eung Kim
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
2024	J	`jnl`	Monet: Mixture of Monosemantic Experts for Transformers. CoRR Jungwoo Park, Youngjin Ahn, Kee-Eung Kim, Jaewoo Kang
2024	J	`jnl`	Stitching Sub-Trajectories with Conditional Diffusion Model for Goal-Conditioned Offline RL. CoRR Sungyoon Kim, Yunseon Choi, Daiki E. Matsunaga, Kee-Eung Kim
2024	A*	`conf`	Stitching Sub-trajectories with Conditional Diffusion Model for Goal-Conditioned Offline RL. AAAI Sungyoon Kim, Yunseon Choi, Daiki E. Matsunaga, Kee-Eung Kim
2024	A	`conf`	SyncVSR: Data-Efficient Visual Speech Recognition with End-to-End Crossmodal Audio Token Synchronization. INTERSPEECH Youngjin Ahn, Jungwoo Park, Sangha Park, Jonghyun Choi, Kee-Eung Kim
2024	J	`jnl`	SyncVSR: Data-Efficient Visual Speech Recognition with End-to-End Crossmodal Audio Token Synchronization. CoRR Youngjin Ahn, Jungwoo Park, Sangha Park, Jonghyun Choi, Kee-Eung Kim
2024	J	`jnl`	Zero-Shot Multi-Hop Question Answering via Monte-Carlo Tree Search with Large Language Models. CoRR Seongmin Lee, Jaewook Shin, Youngjin Ahn, Seokin Seo, Ohjoon Kwon, Kee-Eung Kim
2023	J	`jnl`	Adapting Text-based Dialogue State Tracker for Spoken Dialogues. CoRR Jaeseok Yoon, Seunghyun Hwang, Ran Han, Jeonguk Bang, 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	—	`conf`	Bayesian Multi-Task Transfer Learning for Soft Prompt Tuning. EMNLP (Findings) Haeju Lee, Minchan Jeong, Se-Young Yun, Kee-Eung Kim
2023	A*	`conf`	Information-Theoretic State Space Model for Multi-View Reinforcement Learning. ICML HyeongJoo Hwang, Seokin Seo, Youngsoo Jang, Sungyoon Kim, Geon-Hyeong Kim, Seunghoon Hong, Kee-Eung Kim
2023	A*	`conf`	Regularized Behavior Cloning for Blocking the Leakage of Past Action Information. NeurIPS Seokin Seo, HyeongJoo Hwang, Hongseok Yang, Kee-Eung Kim
2023	A*	`conf`	Trustworthy Residual Vehicle Value Prediction for Auto Finance. AAAI Mihye Kim, Jimyung Choi, Jaehyun Kim, Wooyoung Kim, Yeonung Baek, Gisuk Bang, Kwangwoon Son, Yeonman Ryou, Kee-Eung Kim
2023	J	`jnl`	Trustworthy residual vehicle value prediction for auto finance. AI Mag. Mihye Kim, Jimyung Choi, Jaehyun Kim, Wooyoung Kim, Yeonung Baek, Gisuk Bang, Kwangwoon Son, Yeonman Ryou, Kee-Eung Kim
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`	Data Augmentation for Learning to Play in Text-Based Games. IJCAI Jinhyeon Kim, Kee-Eung Kim
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	—	`conf`	Learning to Embed Multi-Modal Contexts for Situated Conversational Agents. NAACL-HLT (Findings) Haeju Lee, Oh Joon Kwon, Yunseon Choi, Minho Park, Ran Han, Yoonhyung Kim, Jinhyeon Kim, Youngjune Lee, Haebin Shin, Kangwook 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
2022	A*	`conf`	PAC-Net: A Model Pruning Approach to Inductive Transfer Learning. ICML Sanghoon Myung, In Huh, Wonik Jang, Jae Myung Choe, Jisu Ryu, Daesin Kim, Kee-Eung Kim, Changwook Jeong
2022	J	`jnl`	PAC-Net: A Model Pruning Approach to Inductive Transfer Learning. CoRR Sanghoon Myung, In Huh, Wonik Jang, Jae Myung Choe, Jisu Ryu, Daesin Kim, Kee-Eung Kim, Changwook Jeong
2022	A*	`conf`	Structure-Aware Transformer Policy for Inhomogeneous Multi-Task Reinforcement Learning. ICLR Sunghoon Hong, Deunsol Yoon, Kee-Eung Kim
2021	J	`jnl`	Augment & Valuate : A Data Enhancement Pipeline for Data-Centric AI. CoRR Youngjune Lee, Oh Joon Kwon, Haeju Lee, Joonyoung Kim, Kangwook Lee, Kee-Eung Kim
2021	J	`jnl`	Corrigendum to 'Extensions to Hybrid Code Networks for FAIR Dialog Data' Computer Speech & Language volume 53 (2019) Pages 80-91. Comput. Speech Lang. Jiyeon Ham, Soohyun Lim, Kyeng-Hun Lee, Kee-Eung Kim
2021	A	`conf`	Dual Correction Strategy for Ranking Distillation in Top-N Recommender System. CIKM Youngjune Lee, Kee-Eung Kim
2021	J	`jnl`	Dual Correction Strategy for Ranking Distillation in Top-N Recommender System. CoRR Youngjune Lee, 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`	Multi-View Representation Learning via Total Correlation Objective. NeurIPS HyeongJoo Hwang, Geon-Hyeong Kim, Seunghoon Hong, 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	C	`conf`	Personalized Treatment Using Biologics: An Analysis Using Counterfactual Regression Based on Deep Learning. ICIS Seongho Eun, Bon San Koo, Ji Seon Oh, Kee-Eung Kim, Byungtae Lee
2021	A*	`conf`	Representation Balancing Offline Model-based Reinforcement Learning. ICLR Byung-Jun Lee, Jongmin Lee, Kee-Eung Kim
2021	A*	`conf`	Winning the L2RPN Challenge: Power Grid Management via Semi-Markov Afterstate Actor-Critic. ICLR Deunsol Yoon, Sunghoon Hong, Byung-Jun 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	A*	`conf`	End-to-End Neural Pipeline for Goal-Oriented Dialogue Systems using GPT-2. ACL Donghoon Ham, Jeong-Gwan Lee, Youngsoo Jang, Kee-Eung Kim
2020	J	`jnl`	Foreword: special issue for the journal track of the 11th Asian Conference on Machine Learning (ACML 2019). Mach. Learn. Kee-Eung Kim, Jun Zhu
2020	J	`jnl`	Foreword: special issue for the journal track of the 12th Asian conference on machine learning (ACML 2020). Mach. Learn. Kee-Eung Kim, Vineeth N. Balasubramanian
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
2020	A*	`conf`	Residual Neural Processes. AAAI Byung-Jun Lee, Seunghoon Hong, Kee-Eung Kim
2020	A*	`conf`	Variational Inference for Sequential Data with Future Likelihood Estimates. ICML Geon-Hyeong Kim, Youngsoo Jang, Hongseok Yang, Kee-Eung Kim
2020	A*	`conf`	Variational Interaction Information Maximization for Cross-domain Disentanglement. NeurIPS HyeongJoo Hwang, Geon-Hyeong Kim, Seunghoon Hong, Kee-Eung Kim
2020	J	`jnl`	Variational Interaction Information Maximization for Cross-domain Disentanglement. CoRR HyeongJoo Hwang, Geon-Hyeong Kim, Seunghoon Hong, Kee-Eung Kim
2019	J	`jnl`	A Machine Learning-Based Approach for the Prediction of Acute Coronary Syndrome Requiring Revascularization. J. Medical Syst. Yung-Kyun Noh, Ji Young Park, Byoung Geol Choi, Kee-Eung Kim, Seung-Woon Rha
2019	J	`jnl`	Bayesian optimistic Kullback-Leibler exploration. Mach. Learn. Kanghoon Lee, Geon-Hyeong Kim, Pedro A. Ortega, Daniel D. Lee, Kee-Eung Kim
2019	J	`jnl`	Extensions to hybrid code networks for FAIR dialog dataset. Comput. Speech Lang. Jiyeon Ham, Soohyun Lim, Kyeng-Hun Lee, Kee-Eung Kim
2019	J	`jnl`	Policy Optimization Through Approximated Importance Sampling. CoRR Marcin B. Tomczak, Dongho Kim, Peter Vrancx, 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`	A Bayesian Approach to Generative Adversarial Imitation Learning. NeurIPS Wonseok Jeon, Seokin Seo, Kee-Eung Kim
2018	J	`jnl`	Cross-Language Neural Dialog State Tracker for Large Ontologies Using Hierarchical Attention. IEEE ACM Trans. Audio Speech Lang. Process. Youngsoo Jang, Jiyeon Ham, Byung-Jun Lee, Kee-Eung Kim
2018	A*	`conf`	Imitation Learning via Kernel Mean Embedding. AAAI Kee-Eung Kim, Hyun Soo Park
2018	A*	`conf`	Monte-Carlo Tree Search for Constrained POMDPs. NeurIPS Jongmin Lee, Geon-Hyeong Kim, Pascal Poupart, Kee-Eung Kim
2018	—	`conf`	OP-CAS: Collision Avoidance with Overtaking Maneuvers. ITSC Eun Sang Cha, Kee-Eung Kim, Stefano Longo, Ankur Mehta
2017	A*	`conf`	Constrained Bayesian Reinforcement Learning via Approximate Linear Programming. IJCAI Jongmin Lee, Youngsoo Jang, Pascal Poupart, Kee-Eung Kim
2017	J	`jnl`	Foreword: special issue for the journal track of the 8th Asian conference on machine learning (ACML 2016). Mach. Learn. Robert J. Durrant, Kee-Eung Kim, Geoffrey Holmes, Stephen Marsland, Masashi Sugiyama, Zhi-Hua Zhou
2017	—	`conf`	Generative Local Metric Learning for Kernel Regression. NIPS Yung-Kyun Noh, Masashi Sugiyama, Kee-Eung Kim, Frank C. Park, Daniel D. Lee
2017	A	`conf`	Hierarchically-partitioned Gaussian Process Approximation. AISTATS Byung-Jun Lee, Jongmin Lee, Kee-Eung Kim
2017	B	`conf`	Hybrid modeling and simulation of tactical maneuvers in computer generated force. SMC Jang Won Bae, Bowon Nam, Kee-Eung Kim, Junseok Lee, Il-Chul Moon
2016	A*	`conf`	Bayesian Reinforcement Learning with Behavioral Feedback. IJCAI Teakgyu Hong, Jongmin Lee, Kee-Eung Kim, Pedro A. Ortega, Daniel D. Lee
2016	J	`jnl`	Dialog History Construction with Long-Short Term Memory for Robust Generative Dialog State Tracking. Dialogue Discourse Byung-Jun Lee, Kee-Eung Kim
2016	—	`conf`	Multi-view Automatic Lip-Reading Using Neural Network. ACCV Workshops (2) Daehyun Lee, Jongmin Lee, Kee-Eung Kim
2016	—	`conf`	Neural dialog state tracker for large ontologies by attention mechanism. SLT Youngsoo Jang, Jiyeon Ham, Byung-Jun Lee, Youngjae Chang, Kee-Eung Kim
2016	C	`ed.`	Proceedings of The 8th Asian Conference on Machine Learning, ACML 2016, Hamilton, New Zealand, November 16-18, 2016. ACML Robert J. Durrant, Kee-Eung Kim
2015	A*	`conf`	Approximate Linear Programming for Constrained Partially Observable Markov Decision Processes. AAAI Pascal Poupart, Aarti Malhotra, Pei Pei, Kee-Eung Kim, Bongseok Goh, Michael Bowling
2015	J	`jnl`	Hierarchical Bayesian Inverse Reinforcement Learning. IEEE Trans. Cybern. Jaedeug Choi, Kee-Eung Kim
2015	J	`jnl`	Information-Theoretic Bounded Rationality. CoRR Pedro A. Ortega, Daniel A. Braun, Justin Dyer, Kee-Eung Kim, Naftali Tishby
2015	A	`conf`	Reactive bandits with attitude. AISTATS Pedro A. Ortega, Kee-Eung Kim, Daniel D. Lee
2015	A*	`conf`	Reward Shaping for Model-Based Bayesian Reinforcement Learning. AAAI Hyeoneun Kim, Woosang Lim, Kanghoon Lee, Yung-Kyun Noh, Kee-Eung Kim
2015	A*	`conf`	Tighter Value Function Bounds for Bayesian Reinforcement Learning. AAAI Kanghoon Lee, Kee-Eung Kim
2014	J	`jnl`	Learning to Cooperate via Policy Search. CoRR Leonid Peshkin, Kee-Eung Kim, Nicolas Meuleau, Leslie Pack Kaelbling
2014	—	`conf`	Optimizing Generative Dialog State Tracker via Cascading Gradient Descent. SIGDIAL Conference Byung-Jun Lee, Woosang Lim, Daejoong Kim, Kee-Eung Kim
2013	A*	`conf`	Bayesian Nonparametric Feature Construction for Inverse Reinforcement Learning. IJCAI Jaedeug Choi, Kee-Eung Kim
2013	—	`conf`	Engineering Statistical Dialog State Trackers: A Case Study on DSTC. SIGDIAL Conference Daejoong Kim, Jaedeug Choi, Kee-Eung Kim, Jungsu Lee, Jinho Sohn
2013	J	`jnl`	Learning Finite-State Controllers for Partially Observable Environments CoRR Nicolas Meuleau, Leonid Peshkin, Kee-Eung Kim, Leslie Pack Kaelbling
2013	J	`jnl`	Solving POMDPs by Searching the Space of Finite Policies CoRR Nicolas Meuleau, Kee-Eung Kim, Leslie Pack Kaelbling, Anthony R. Cassandra
2012	J	`jnl`	A Geometric Traversal Algorithm for Reward-Uncertain MDPs CoRR Eunsoo Oh, Kee-Eung Kim
2012	—	`conf`	Cost-Sensitive Exploration in Bayesian Reinforcement Learning. NIPS Dongho Kim, Kee-Eung Kim, Pascal Poupart
2012	J	`jnl`	Exploiting symmetries for single- and multi-agent Partially Observable Stochastic Domains. Artif. Intell. Byung Kon Kang, Kee-Eung Kim
2012	—	`conf`	Nonparametric Bayesian Inverse Reinforcement Learning for Multiple Reward Functions. NIPS Jaedeug Choi, Kee-Eung Kim
2011	A	`conf`	A Geometric Traversal Algorithm for Reward-Uncertain MDPs. UAI Eunsoo Oh, Kee-Eung Kim
2011	A*	`conf`	A POMDP-Based Optimal Control of P300-Based Brain-Computer Interfaces. AAAI Jaeyoung Park, Kee-Eung Kim, Yoon-Kyu Song
2011	A*	`conf`	Closing the Gap: Improved Bounds on Optimal POMDP Solutions. ICAPS Pascal Poupart, Kee-Eung Kim, Dongho Kim
2011	J	`jnl`	Inverse Reinforcement Learning in Partially Observable Environments. J. Mach. Learn. Res. Jaedeug Choi, Kee-Eung Kim
2011	—	`conf`	MAP Inference for Bayesian Inverse Reinforcement Learning. NIPS Jaedeug Choi, Kee-Eung Kim
2011	A*	`conf`	Point-Based Value Iteration for Constrained POMDPs. IJCAI Dongho Kim, Jaesong Lee, Kee-Eung Kim, Pascal Poupart
2011	J	`jnl`	Robust Performance Evaluation of POMDP-Based Dialogue Systems. IEEE ACM Trans. Audio Speech Lang. Process. Dongho Kim, Jin H. Kim, Kee-Eung Kim
2010	A	`conf`	A POMDP approach to P300-based brain-computer interfaces. IUI Jaeyoung Park, Kee-Eung Kim, Sungho Jo
2010	B	`conf`	Point-Based Bounded Policy Iteration for Decentralized POMDPs. PRICAI Youngwook Kim, Kee-Eung Kim
2009	A*	`conf`	Inverse Reinforcement Learning in Partially Observable Environments. IJCAI Jaedeug Choi, Kee-Eung Kim
2008	A	`conf`	Effects of user modeling on POMDP-based dialogue systems. INTERSPEECH Dongho Kim, Hyeong Seop Sim, Kee-Eung Kim, Jin Hyung Kim, Hyunjeong Kim, Joo Won Sung
2008	A*	`conf`	Exploiting Symmetries in POMDPs for Point-Based Algorithms. AAAI Kee-Eung Kim
2008	A*	`conf`	Symbolic Heuristic Search Value Iteration for Factored POMDPs. AAAI Hyeong Seop Sim, Kee-Eung Kim, Jin Hyung Kim, Du-Seong Chang, Myoung-Wan Koo
2007	—	`conf`	Place Recognition Using Multiple Wearable Cameras. UCS Kyungmin Min, Seonghun Lee, Kee-Eung Kim, Jin Hyung Kim
2006	A*	`conf`	Hand Grip Pattern Recognition for Mobile User Interfaces. AAAI Kee-Eung Kim, Wook Chang, Sung-Jung Cho, Junghyun Shim, Hyunjeong Lee, Joonah Park, Youngbeom Lee, Sangryoung Kim
2005	—	`conf`	Variable bandwidth allocation scheme for energy efficient wireless sensor network. ICC SeongHwan Cho, Kee-Eung Kim
2003	J	`jnl`	Solving factored MDPs using non-homogeneous partitions. Artif. Intell. Kee-Eung Kim, Thomas L. Dean
2002	B	`conf`	Solving Factored MDPs with Large Action Space Using Algebraic Decision Diagrams. PRICAI Kee-Eung Kim, Thomas L. Dean
2001	J	`jnl`	Learning to Cooperate via Policy Search CoRR Leonid Peshkin, Kee-Eung Kim, Nicolas Meuleau, Leslie Pack Kaelbling
2001	—	`—`	Representations and Algorithms for Large Stochastic Planning Problems. Kee-Eung Kim
2001	A*	`conf`	Solving Factored MDPs via Non-Homogeneous Partitioning. IJCAI Kee-Eung Kim, Thomas L. Dean
2000	—	`conf`	Approximate Solutions to Factored Markov Decision Processes via Greedy Search in the Space of Finite State Controllers. AIPS Kee-Eung Kim, Thomas L. Dean, Nicolas Meuleau
2000	A	`conf`	Learning to Cooperate via Policy Search. UAI Leonid Peshkin, Kee-Eung Kim, Nicolas Meuleau, Leslie Pack Kaelbling
1999	A	`conf`	Learning Finite-State Controllers for Partially Observable Environments. UAI Nicolas Meuleau, Leonid Peshkin, Kee-Eung Kim, Leslie Pack Kaelbling
1999	A	`conf`	Solving POMDPs by Searching the Space of Finite Policies. UAI Nicolas Meuleau, Kee-Eung Kim, Leslie Pack Kaelbling, Anthony R. Cassandra
1998	—	`conf`	Solving Stochastic Planning Problems with Large State and Action Spaces. AIPS Thomas L. Dean, Robert Givan, Kee-Eung Kim
1998	—	`conf`	Solving Very Large Weakly Coupled Markov Decision Processes. AAAI/IAAI Nicolas Meuleau, Milos Hauskrecht, Kee-Eung Kim, Leonid Peshkin, Leslie Pack Kaelbling, Thomas L. Dean, Craig Boutilier