Kee-Eung Kim

Publication Activity (10 Years)

Years Active: 1998-2024
Publications (10 Years): 79

Top Venues

CoRR

AAAI

NeurIPS

ICLR

Publications

Sungyoon Kim, Yunseon Choi, Daiki E. Matsunaga, Kee-Eung Kim
Stitching Sub-Trajectories with Conditional Diffusion Model for Goal-Conditioned Offline RL. CoRR (2024)
Haeju Lee, Minchan Jeong, Se-Young Yun, Kee-Eung Kim
Bayesian Multi-Task Transfer Learning for Soft Prompt Tuning. CoRR (2024)
Young Jin Ahn, Jungwoo Park, Sangha Park, Jonghyun Choi, Kee-Eung Kim
SyncVSR: Data-Efficient Visual Speech Recognition with End-to-End Crossmodal Audio Token Synchronization. CoRR (2024)
Yunseon Choi, Sangmin Bae, Seonghyun Ban, Minchan Jeong, Chuheng Zhang, Lei Song, Li Zhao, Jiang Bian, Kee-Eung Kim
Hard Prompts Made Interpretable: Sparse Entropy Regularization for Prompt Tuning with RL. ACL (1) (2024)
Sungyoon Kim, Yunseon Choi, Daiki E. Matsunaga, Kee-Eung Kim
Stitching Sub-trajectories with Conditional Diffusion Model for Goal-Conditioned Offline RL. AAAI (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. 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)
Yunseon Choi, Sangmin Bae, Seonghyun Ban, Minchan Jeong, Chuheng Zhang, Lei Song, Li Zhao, Jiang Bian, Kee-Eung Kim
Hard Prompts Made Interpretable: Sparse Entropy Regularization for Prompt Tuning with RL. CoRR (2024)
Kyungsik Lee, Hana Yoo, Sumin Shin, Wooyoung Kim, Yeonung Baek, Hyunjin Kang, Jaehyun Kim, Kee-Eung Kim
A Submodular Optimization Approach to Accountable Loan Approval. AAAI (2024)
Haeju Lee, Minchan Jeong, Se-Young Yun, Kee-Eung Kim
Bayesian Multi-Task Transfer Learning for Soft Prompt Tuning. EMNLP (Findings) (2023)
Mihye Kim, Jimyung Choi, Jaehyun Kim, Wooyoung Kim, Yeonung Baek, Gisuk Bang, Kwangwoon Son, Yeonman Ryou, Kee-Eung Kim
Trustworthy residual vehicle value prediction for auto finance. AI Mag. 44 (4) (2023)
Seokin Seo, HyeongJoo Hwang, Hongseok Yang, Kee-Eung Kim
Regularized Behavior Cloning for Blocking the Leakage of Past Action Information. NeurIPS (2023)
HyeongJoo Hwang, Seokin Seo, Youngsoo Jang, Sungyoon Kim, Geon-Hyeong Kim, Seunghoon Hong, Kee-Eung Kim
Information-Theoretic State Space Model for Multi-View Reinforcement Learning. ICML (2023)
Jaeseok Yoon, Seunghyun Hwang, Ran Han, Jeonguk Bang, Kee-Eung Kim
Adapting Text-based Dialogue State Tracker for Spoken Dialogues. CoRR (2023)
Daiki E. Matsunaga, Jongmin Lee, Jaeseok Yoon, Stefanos Leonardos, Pieter Abbeel, Kee-Eung Kim
AlberDICE: Addressing Out-Of-Distribution Joint Actions in Offline Multi-Agent RL via Alternating Stationary Distribution Correction Estimation. NeurIPS (2023)
Daiki E. Matsunaga, Jongmin Lee, Jaeseok Yoon, Stefanos Leonardos, Pieter Abbeel, Kee-Eung Kim
AlberDICE: Addressing Out-Of-Distribution Joint Actions in Offline Multi-Agent RL via Alternating Stationary Distribution Correction Estimation. CoRR (2023)
Mihye Kim, Jimyung Choi, Jaehyun Kim, Wooyoung Kim, Yeonung Baek, Gisuk Bang, Kwangwoon Son, Yeonman Ryou, Kee-Eung Kim
Trustworthy Residual Vehicle Value Prediction for Auto Finance. AAAI (2023)
Sanghoon Myung, In Huh, Wonik Jang, Jae Myung Choe, Jisu Ryu, Daesin Kim, Kee-Eung Kim, Changwook Jeong
PAC-Net: A Model Pruning Approach to Inductive Transfer Learning. ICML (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. 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)
Haeju Lee, Oh Joon Kwon, Yunseon Choi, Minho Park, Ran Han, Yoonhyung Kim, Jinhyeon Kim, Youngjune Lee, Haebin Shin, Kangwook Lee, Kee-Eung Kim
Learning to Embed Multi-Modal Contexts for Situated Conversational Agents. NAACL-HLT (Findings) (2022)
Jinhyeon Kim, Kee-Eung Kim
Data Augmentation for Learning to Play in Text-Based Games. IJCAI (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)
Sunghoon Hong, Deunsol Yoon, Kee-Eung Kim
Structure-Aware Transformer Policy for Inhomogeneous Multi-Task Reinforcement Learning. ICLR (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)
Sanghoon Myung, In Huh, Wonik Jang, Jae Myung Choe, Jisu Ryu, Daesin Kim, Kee-Eung Kim, Changwook Jeong
PAC-Net: A Model Pruning Approach to Inductive Transfer Learning. CoRR (2022)
Jongmin Lee, Wonseok Jeon, Byung-Jun Lee, Joelle Pineau, Kee-Eung Kim
OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation. CoRR (2021)
Youngjune Lee, Kee-Eung Kim
Dual Correction Strategy for Ranking Distillation in Top-N Recommender System. CoRR (2021)
Youngjune Lee, Kee-Eung Kim
Dual Correction Strategy for Ranking Distillation in Top-N Recommender System. CIKM (2021)
HyeongJoo Hwang, Geon-Hyeong Kim, Seunghoon Hong, Kee-Eung Kim
Multi-View Representation Learning via Total Correlation Objective. NeurIPS (2021)
Deunsol Yoon, Sunghoon Hong, Byung-Jun Lee, Kee-Eung Kim
Winning the L2RPN Challenge: Power Grid Management via Semi-Markov Afterstate Actor-Critic. ICLR (2021)
Byung-Jun Lee, Jongmin Lee, Kee-Eung Kim
Representation Balancing Offline Model-based Reinforcement Learning. ICLR (2021)
Seongho Eun, Bon San Koo, Ji Seon Oh, Kee-Eung Kim, Byungtae Lee
Personalized Treatment Using Biologics: An Analysis Using Counterfactual Regression Based on Deep Learning. ICIS (2021)
Youngjune Lee, Oh Joon Kwon, Haeju Lee, Joonyoung Kim, Kangwook Lee, Kee-Eung Kim
Augment & Valuate : A Data Enhancement Pipeline for Data-Centric AI. CoRR (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)
Jiyeon Ham, Soohyun Lim, Kyeng-Hun Lee, Kee-Eung Kim
Corrigendum to 'Extensions to Hybrid Code Networks for FAIR Dialog Data' Computer Speech & Language volume 53 (2019) Pages 80-91. Comput. Speech Lang. 65 (2021)
Jongmin Lee, Byung-Jun Lee, Kee-Eung Kim
Reinforcement Learning for Control with Multiple Frequencies. NeurIPS (2020)
Byung-Jun Lee, Seunghoon Hong, Kee-Eung Kim
Residual Neural Processes. AAAI (2020)
Youngsoo Jang, Jongmin Lee, Kee-Eung Kim
Bayes-Adaptive Monte-Carlo Planning and Learning for Goal-Oriented Dialogues. AAAI (2020)
DongHoon Ham, Jeong-Gwan Lee, Youngsoo Jang, Kee-Eung Kim
End-to-End Neural Pipeline for Goal-Oriented Dialogue Systems using GPT-2. ACL (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)
Kee-Eung Kim, Vineeth N. Balasubramanian
Foreword: special issue for the journal track of the 12th Asian conference on machine learning (ACML 2020). Mach. Learn. 109 (12) (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)
HyeongJoo Hwang, Geon-Hyeong Kim, Seunghoon Hong, Kee-Eung Kim
Variational Interaction Information Maximization for Cross-domain Disentanglement. CoRR (2020)
Kee-Eung Kim, Jun Zhu
Foreword: special issue for the journal track of the 11th Asian Conference on Machine Learning (ACML 2019). Mach. Learn. 109 (3) (2020)
Geon-Hyeong Kim, Youngsoo Jang, Hongseok Yang, Kee-Eung Kim
Variational Inference for Sequential Data with Future Likelihood Estimates. ICML (2020)
HyeongJoo Hwang, Geon-Hyeong Kim, Seunghoon Hong, Kee-Eung Kim
Variational Interaction Information Maximization for Cross-domain Disentanglement. NeurIPS (2020)
Jiyeon Ham, Soohyun Lim, Kyeng-Hun Lee, Kee-Eung Kim
Extensions to hybrid code networks for FAIR dialog dataset. Comput. Speech Lang. 53 (2019)
Yung-Kyun Noh, Ji Young Park, Byoung Geol Choi, Kee-Eung Kim, Seung-Woon Rha
A Machine Learning-Based Approach for the Prediction of Acute Coronary Syndrome Requiring Revascularization. J. Medical Syst. 43 (8) (2019)
Marcin B. Tomczak, Dongho Kim, Peter Vrancx, Kee-Eung Kim
Policy Optimization Through Approximated Importance Sampling. CoRR (2019)
Kanghoon Lee, Geon-hyeong Kim, Pedro A. Ortega, Daniel D. Lee, Kee-Eung Kim
Bayesian optimistic Kullback-Leibler exploration. Mach. Learn. 108 (5) (2019)
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)
Eun Sang Cha, Kee-Eung Kim, Stefano Longo, Ankur Mehta
OP-CAS: Collision Avoidance with Overtaking Maneuvers. ITSC (2018)
Youngsoo Jang, Jiyeon Ham, Byung-Jun Lee, Kee-Eung Kim
Cross-Language Neural Dialog State Tracker for Large Ontologies Using Hierarchical Attention. IEEE ACM Trans. Audio Speech Lang. Process. 26 (11) (2018)
Wonseok Jeon, Seokin Seo, Kee-Eung Kim
A Bayesian Approach to Generative Adversarial Imitation Learning. NeurIPS (2018)
Jongmin Lee, Geon-hyeong Kim, Pascal Poupart, Kee-Eung Kim
Monte-Carlo Tree Search for Constrained POMDPs. NeurIPS (2018)
Kee-Eung Kim, Hyun Soo Park
Imitation Learning via Kernel Mean Embedding. AAAI (2018)
Byung-Jun Lee, Jongmin Lee, Kee-Eung Kim
Hierarchically-partitioned Gaussian Process Approximation. AISTATS (2017)
Yung-Kyun Noh, Masashi Sugiyama, Kee-Eung Kim, Frank C. Park, Daniel D. Lee
Generative Local Metric Learning for Kernel Regression. NIPS (2017)
Jongmin Lee, Youngsoo Jang, Pascal Poupart, Kee-Eung Kim
Constrained Bayesian Reinforcement Learning via Approximate Linear Programming. IJCAI (2017)
Robert J. Durrant, Kee-Eung Kim, Geoffrey Holmes, Stephen Marsland, Masashi Sugiyama, Zhi-Hua Zhou
Foreword: special issue for the journal track of the 8th Asian conference on machine learning (ACML 2016). Mach. Learn. 106 (5) (2017)
Jang Won Bae, Bowon Nam, Kee-Eung Kim, Junseok Lee, Il-Chul Moon
Hybrid modeling and simulation of tactical maneuvers in computer generated force. SMC (2017)
Teakgyu Hong, Jongmin Lee, Kee-Eung Kim, Pedro A. Ortega, Daniel D. Lee
Bayesian Reinforcement Learning with Behavioral Feedback. IJCAI (2016)
Byung-Jun Lee, Kee-Eung Kim
Dialog History Construction with Long-Short Term Memory for Robust Generative Dialog State Tracking. Dialogue Discourse 7 (3) (2016)
Daehyun Lee, Jongmin Lee, Kee-Eung Kim
Multi-view Automatic Lip-Reading Using Neural Network. ACCV Workshops (2) (2016)
Youngsoo Jang, Jiyeon Ham, Byung-Jun Lee, Youngjae Chang, Kee-Eung Kim
Neural dialog state tracker for large ontologies by attention mechanism. SLT (2016)
Kanghoon Lee, Kee-Eung Kim
Tighter Value Function Bounds for Bayesian Reinforcement Learning. AAAI (2015)
Pedro A. Ortega, Daniel A. Braun, Justin Dyer, Kee-Eung Kim, Naftali Tishby
Information-Theoretic Bounded Rationality. CoRR (2015)
Pascal Poupart, Aarti Malhotra, Pei Pei, Kee-Eung Kim, Bongseok Goh, Michael Bowling
Approximate Linear Programming for Constrained Partially Observable Markov Decision Processes. AAAI (2015)
Pedro A. Ortega, Kee-Eung Kim, Daniel D. Lee
Reactive bandits with attitude. AISTATS (2015)
Jaedeug Choi, Kee-Eung Kim
Hierarchical Bayesian Inverse Reinforcement Learning. IEEE Trans. Cybern. 45 (4) (2015)
Hyeoneun Kim, Woosang Lim, Kanghoon Lee, Yung-Kyun Noh, Kee-Eung Kim
Reward Shaping for Model-Based Bayesian Reinforcement Learning. AAAI (2015)
Byung-Jun Lee, Woosang Lim, Daejoong Kim, Kee-Eung Kim
Optimizing Generative Dialog State Tracker via Cascading Gradient Descent. SIGDIAL Conference (2014)
Leonid Peshkin, Kee-Eung Kim, Nicolas Meuleau, Leslie Pack Kaelbling
Learning to Cooperate via Policy Search. CoRR (2014)
Jaedeug Choi, Kee-Eung Kim
Bayesian Nonparametric Feature Construction for Inverse Reinforcement Learning. IJCAI (2013)
Nicolas Meuleau, Leonid Peshkin, Kee-Eung Kim, Leslie Pack Kaelbling
Learning Finite-State Controllers for Partially Observable Environments CoRR (2013)
Daejoong Kim, Jaedeug Choi, Kee-Eung Kim, Jungsu Lee, Jinho Sohn
Engineering Statistical Dialog State Trackers: A Case Study on DSTC. SIGDIAL Conference (2013)
Nicolas Meuleau, Kee-Eung Kim, Leslie Pack Kaelbling, Anthony R. Cassandra
Solving POMDPs by Searching the Space of Finite Policies CoRR (2013)
Eunsoo Oh, Kee-Eung Kim
A Geometric Traversal Algorithm for Reward-Uncertain MDPs CoRR (2012)
Dongho Kim, Kee-Eung Kim, Pascal Poupart
Cost-Sensitive Exploration in Bayesian Reinforcement Learning. NIPS (2012)
Byung Kon Kang, Kee-Eung Kim
Exploiting symmetries for single- and multi-agent Partially Observable Stochastic Domains. Artif. Intell. (2012)
Jaedeug Choi, Kee-Eung Kim
Nonparametric Bayesian Inverse Reinforcement Learning for Multiple Reward Functions. NIPS (2012)
Dongho Kim, Jaesong Lee, Kee-Eung Kim, Pascal Poupart
Point-Based Value Iteration for Constrained POMDPs. IJCAI (2011)
Dongho Kim, Jin H. Kim, Kee-Eung Kim
Robust Performance Evaluation of POMDP-Based Dialogue Systems. IEEE ACM Trans. Audio Speech Lang. Process. 19 (4) (2011)
Jaeyoung Park, Kee-Eung Kim, Yoon-Kyu Song
A POMDP-Based Optimal Control of P300-Based Brain-Computer Interfaces. AAAI (2011)
Pascal Poupart, Kee-Eung Kim, Dongho Kim
Closing the Gap: Improved Bounds on Optimal POMDP Solutions. ICAPS (2011)
Jaedeug Choi, Kee-Eung Kim
Inverse Reinforcement Learning in Partially Observable Environments. J. Mach. Learn. Res. 12 (2011)
Jaedeug Choi, Kee-Eung Kim
MAP Inference for Bayesian Inverse Reinforcement Learning. NIPS (2011)
Eunsoo Oh, Kee-Eung Kim
A Geometric Traversal Algorithm for Reward-Uncertain MDPs. UAI (2011)
Youngwook Kim, Kee-Eung Kim
Point-Based Bounded Policy Iteration for Decentralized POMDPs. PRICAI (2010)
Jaeyoung Park, Kee-Eung Kim, Sungho Jo
A POMDP approach to P300-based brain-computer interfaces. IUI (2010)
Jaedeug Choi, Kee-Eung Kim
Inverse Reinforcement Learning in Partially Observable Environments. IJCAI (2009)
Hyeong Seop Sim, Kee-Eung Kim, Jin Hyung Kim, Du-Seong Chang, Myoung-Wan Koo
Symbolic Heuristic Search Value Iteration for Factored POMDPs. AAAI (2008)

Kee-Eung Kim.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Kee-Eung Kim