Seongmin Lee*, Jaewook Shin*, Youngjin Ahn, Seokin Seo, Ohjoon Kwon, Kee-Eung Kim: Zero-Shot Multi-Hop Question Answering via Monte-Carlo Tree Search with Large Language Models. arXiv. 2024. [📄 Abstract] [✏️ Paper]
Seonghyun Ban*, Heesan Kong*, Kee-Eung Kim: Data Augmentation with Diffusion for Open-Set Semi-Supervised Learning. Advances in Neural Information Processing Systems (NeurIPS) (to appear). 2024. [📄 Abstract]
Seokin Seo, Byung-Jun Lee, Jongmin Lee, HyeongJoo Hwang, Hongseok Yang, Kee-Eung Kim: Mitigating Covariate Shift in Behavioral Cloning via Robust Stationary Distribution Correction. Advances in Neural Information Processing Systems (NeurIPS) (to appear). 2024. [📄 Abstract]
Oh Joon Kwon, Daiki E. Matsunaga, Kee-Eung Kim: GDPO: Learning to Align Language Models with Diversity Using GFlowNets. Empirical Methods in Natural Language Procesesing (EMNLP) (to appear). 2024. [📄 Abstract] [✏️ Paper]
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. Interspeech. 2024. [📄 Abstract] [✏️ Paper]
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. Association for Computational Linguistics (ACL). 2024. Oral presentation [📄 Abstract] [✏️ Paper]
Yunseon Choi, Li Zhao, Chuheng Zhang, Lei Song, Jiang Bian, Kee-Eung Kim: Diversification of Adaptive Policy for Effective Offline Reinforcement Learning. International Joint Conference on Artificial Intelligence (IJCAI). 2024. [📄 Abstract] [✏️ Paper]
최윤선, 황두환, 김기응: 디퓨전 모델의 소량 데이터 학습자로서 활용한 다양한 데모 데이터로부터의 오프라인 모사 학습. 한국컴퓨터종합학술대회(KCC). 2024. [📄 Abstract] [✏️ Paper]
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. International Conference on Learning Representations (ICLR). 2024. Spotlight [📄 Abstract] [✏️ Paper]
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. IAAI Technical Track on Deployed Highly Innovative Applications of AI (IAAI). 2024. Innovative application award [📄 Abstract] [✏️ Paper]
Sungyoon Kim, Yunseon Choi, Daiki E. Matsunaga, Kee-Eung Kim: Stitching Sub-Trajectories with Conditional Diffusion Model for Goal-Conditioned Offline RL. AAAI Conference on Artificial Intelligence. 2024. [📄 Abstract] [✏️ Paper]
윤재석, 황승현, 김기응: 대규모 언어 모델을 활용한 음성 기반 대화 시스템의 가능성 연구. 한국통신학회. 2024. [📄 Abstract] [✏️ Paper]
최윤선, 반성현, 김기응: 해석 가능한 프롬프트 최적화에 관한 강화학습 연구. 한국소프트웨어종합학술대회(KSC) 2023, 한국정보과학회. 2023. [📄 Abstract] [✏️ Paper]
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 Magazine. 2023. [📄 Abstract] [✏️ Paper]
Haeju Lee*, Minchan Jeong*, Se-Young Yun, and Kee-Eung Kim: Bayesian Multi-Task Transfer Learning for Soft Prompt Tuning. Findings of Empirical Methods in Natural Language Processing (EMNLP). 2023. [📄 Abstract] [✏️ Paper]
Seokin Seo, HyeongJoo Hwang, Hongseok Yang, and Kee-Eung Kim: Regularized Behavior Cloning for Blocking the Leakage of Past Action Information. Advances in Neural Information Processing Systems (NeurIPS). 2023. Spotlight [📄 Abstract] [✏️ Paper] [🧑💻 Code]
Daiki E. Matsunaga*, Jongmin Lee*, Jaeseok Yoon, Stefanos Leonardos, Pieter Abbeel, and Kee-Eung Kim: AlberDICE: Addressing Out-Of-Distribution Joint Actions in Offline Multi-Agent RL via Alternating Stationary Distribution Correction Estimation. Advances in Neural Information Processing Systems (NeurIPS). 2023. [📄 Abstract] [✏️ Paper] [🧑💻 Code]
Jaeseok Yoon*, Seunghyun Hwang*, Ran Han, Jeonguk Bang, and Kee-Eung Kim: Adapting Text-based Dialogue State Tracker for Spoken Dialogues. Special Interest Group on Discourse and Dialogue (SIGDIAL) DSTC11 Workshop. 2023. Track best paper [📄 Abstract] [✏️ Paper]
HyeongJoo Hwang, Seokin Seo, Youngsoo Jang, Sungyoon Kim, Geon-Hyeong Kim, Seunghoon Hong, and Kee-Eung Kim: Information-Theoretic State Space Model for Multi-View Reinforcement Learning. Proceedings of International Conference on Machine Learning (ICML). 2023. Oral presentation [📄 Abstract] [✏️ Paper] [🧑💻 Code]
Mihye Kim, Jimyung Choi, Jaehyun Kim, Wooyoung Kim, Yeonung Baek, Gisuk Bang, Kwangwoon Son, Yeonman Ryou, and Kee-Eung Kim: Trustworthy Residual Vehicle Value Prediction for Auto Finance. Proceedings of IAAI Technical Track on deployed Highly Innovative Applications of AI. 2023. Innovative application award [📄 Abstract] [✏️ Paper]
서석인, 황형주, 양홍석, and 김기응: 특징조합 교란자 균형을 통한 인과정규화된 로지스틱 회귀 개선. 한국소프트웨어종합학술대회(KSC) 2022, 한국정보과학회. 2022. [📄 Abstract] [✏️ Paper]
Geon-Hyeong Kim*, Jongmin Lee*, Youngsoo Jang, Hongseok Yang, and Kee-Eung Kim: LobsDICE: Offline Learning from Observation via Stationary Distribution Correction Estimation. Advances in Neural Information Processing Systems (NeurIPS). 2022. [📄 Abstract] [✏️ Paper] [🧑💻 Code]
Haanvid Lee, Jongmin Lee, Yunseon Choi, Wonseok Jeon, Byung-Jun Lee, Yung-Kyun Noh, and Kee-Eung Kim: Local Metric Learning for Off-Policy Evaluation in Contextual Bandits with Continuous Actions. Advances in Neural Information Processing Systems (NeurIPS). 2022. [📄 Abstract] [✏️ Paper] [🧑💻 Code]
Sanghoon Myung, In Huh, Wonik Jang, Jae Myung Choe, Jisu Ryu, Daesin Kim, Kee-Eung Kim, and Changwook Jeong: PAC-Net: A Model Pruning Approach to Inductive Transfer Learning. Proceedings of International Conference on Machine Learning (ICML). 2022. [📄 Abstract] [✏️ Paper]
Jinhyeon Kim and Kee-Eung Kim: Data Augmentation for Learning to Play in Text-Based Games. Proceedings of International Joint Conference on Artificial Intelligence (IJCAI). 2022. [📄 Abstract] [✏️ Paper]
Haeju Lee*, Oh Joon Kwon*, Yunseon Choi*, Minho Park, Ran Han, Yoonhyung Kim, Jinhyeon Kim, Youngjune Lee, Haebin Shin, Kangwook Lee, and Kee-Eung Kim: Learning to Embed Multi-Modal Contexts for Situated Conversational Agents. Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL) Findings. 2022. [📄 Abstract] [✏️ Paper]
Haeju Lee*, Oh Joon Kwon*, Yunseon Choi*, Jinhyeon Kim, Youngjune Lee, Ran Han, Yoonhyung Kim, Minho Park, Kangwook Lee, Haebin Shin, and Kee-Eung Kim: Tackling Situated Multi-Modal Task-Oriented Dialogs with a Single Transformer Model. AAAI Conference on Artificial Intelligence (AAAI) DSTC10 Workshop. 2022. Track best paper [📄 Abstract] [✏️ Paper]
Sunghoon Hong, Deunsol Yoon, and Kee-Eung Kim: Structure-Aware Transformer Policy for Inhomogeneous Multi-Task Reinforcement Learning. International Conference on Learning Representations (ICLR). 2022. [📄 Abstract] [✏️ Paper]
Youngsoo Jang, Jongmin Lee, and Kee-Eung Kim: GPT-Critic: Offline Reinforcement Learning for End-to-End Task-Oriented Dialogue Systems. International Conference on Learning Representations (ICLR). 2022. [📄 Abstract] [✏️ Paper] [🧑💻 Code]
Geon-Hyeong Kim, Seokin Seo, Jongmin Lee, Wonseok Jeon, HyeongJoo Hwang, Hongseok Yang, and Kee-Eung Kim: DemoDICE: Offline Imitation Learning with Supplementary Imperfect Demonstrations. International Conference on Learning Representations (ICLR). 2022. [📄 Abstract] [✏️ Paper] [🧑💻 Code]
Jongmin Lee, Cosmin Paduraru, Daniel J. Mankowitz, Nicolas Heess, Doina Precup, Kee-Eung Kim, and Arthur Guez: COptiDICE: Offline Constrained Reinforcement Learning via Stationary Distribution Correction Estimation. International Conference on Learning Representations (ICLR). 2022. Spotlight [📄 Abstract] [✏️ Paper]
HyeongJoo Hwang, Geon-Hyeong Kim, Seunghoon Hong, and Kee-Eung Kim: Multi-View Representation Learning via Total Correlation Objective. Advances in Neural Information Processing Systems (NeurIPS). 2021. [📄 Abstract] [✏️ Paper]
김건형, 장영수, 이종민, and 김기응: 효율적인 다중태스크 오프라인 모델기반 강화학습 알고리즘에 대한 연구. 한국소프트웨어종합학술대회, 한국정보과학회. 2021. [📄 Abstract] [✏️ Paper]
Youngjune Lee, Oh Joon Kwon, Haeju Lee, Joonyoung Kim, Kangwook Lee, and Kee-Eung Kim: Augment & Valuate : A Data Enhancement Pipeline for Data-Centric AI. Neural Information Processing Systems (NeurIPS) Data-Centric AI workshop. 2021. Honorable mention [📄 Abstract] [✏️ Paper]
Youngjune Lee and Kee-Eung Kim: Dual Correction Strategy for Ranking Distillation in Top-N Recommender System. Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM). 2021. [📄 Abstract] [✏️ Paper]
Jongmin Lee*, Wonseok Jeon*, Byung-Jun Lee, Joelle Pineau, and Kee-Eung Kim: OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation. Proceedings of the International Conference on Machine Learning (ICML). 2021. [📄 Abstract] [✏️ Paper]
Jongmin Lee*, Wonseok Jeon*, Byung-Jun Lee, Joelle Pineau, and Kee-Eung Kim: OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation. A Roadmap to Never-Ending RL Workshop at ICLR. 2021. [📄 Abstract] [✏️ Paper]
Jinhyeon Kim, Donghoon Ham, Jeong-Gwan Lee, and Kee-Eung Kim: End-to-End Document-Grounded Conversation with Encoder-Decoder Pre-Trained Language Model. AAAI Conference on Artificial Intelligence (AAAI) DSTC9 Workshop. 2021. [📄 Abstract] [✏️ Paper]
Deunsol Yoon*, Sunghoon Hong*, Byung-Jun Lee, and Kee-Eung Kim: Winning the L2RPN Challenge: Power Grid Management via Semi-Markov Afterstate Actor-Critic. International Conference on Learning Representations (ICLR). 2021. Spotlight [📄 Abstract] [✏️ Paper]
Youngsoo Jang, Seokin Seo, Jongmin Lee, and Kee-Eung Kim: Monte-Carlo Planning and Learning with Language Action Value Estimates. International Conference on Learning Representations (ICLR). 2021. [📄 Abstract] [✏️ Paper]
Byung-Jun Lee, Jongmin Lee, and Kee-Eung Kim: Representation Balancing Offline Model-based Reinforcement Learning. International Conference on Learning Representations (ICLR). 2021. [📄 Abstract] [✏️ Paper]
이병준, 이종민, 최윤선, 장영수, and 김기응: 효율적인 평생학습 알고리즘의 모델기반 강화학습 적용에 관한 연구. 한국소프트웨어종합학술대회, 한국정보과학회. 2020. [📄 Abstract] [✏️ Paper]
HyeongJoo Hwang, Geon-Hyeong Kim, Seunghoon Hong, and Kee-Eung Kim: Variational Interaction Information Maximization for Cross-domain Disentanglement. Advances in Neural Information Processing Systems (NeurIPS). 2020. [📄 Abstract] [✏️ Paper]
Jongmin Lee, Byung-Jun Lee, and Kee-Eung Kim: Reinforcement Learning for Control with Multiple Frequencies. Advances in Neural Information Processing Systems (NeurIPS). 2020. [📄 Abstract] [✏️ Paper]
Geon-Hyeong Kim, Youngsoo Jang, Hongseok Yang, and Kee-Eung Kim: Variational Inference for Sequential Data with Future Likelihood Estimates. Proceedings of the International Conference on Machine Learning (ICML). 2020. [📄 Abstract] [✏️ Paper]
Byung-Jun Lee*, Jongmin Lee*, Peter Vrancx, Dongho Kim, and Kee-Eung Kim: Batch Reinforcement Learning with Hyperparameter Gradients. Proceedings of the International Conference on Machine Learning (ICML). 2020. [📄 Abstract] [✏️ Paper] [🧑💻 Code]
Donghoon Ham*, Jeong-Gwan Lee*, Youngsoo Jang, and Kee-Eung Kim: End-to-End Neural Pipeline for Goal-Oriented Dialogue System using GPT-2. Annual Conference of the Association for Computational Linguistics (ACL). 2020. [📄 Abstract] [✏️ Paper]
Donghoon Ham*, Jeong-Gwan Lee*, Youngsoo Jang, and Kee-Eung Kim: End-to-End Neural Pipeline for Goal-Oriented Dialogue System using GPT-2. AAAI Conference on Artificial Intelligence (AAAI) DSTC8 Workshop. 2020. [📄 Abstract] [✏️ Paper]
Byung-Jun Lee, Seunghoon Hong, and Kee-Eung Kim: Residual Neural Processes. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI). 2020. [📄 Abstract] [✏️ Paper]
Youngsoo Jang, Jongmin Lee, and Kee-Eung Kim: Bayes-Adaptive Monte-Carlo Planning and Learning for Goal-Oriented Dialogues. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI). 2020. [📄 Abstract] [✏️ Paper]
Jongmin Lee, Wonseok Jeon, Geon-Hyeong Kim, and Kee-Eung Kim: Monte-Carlo Tree Search in Continuous Action Spaces with Value Gradients. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI). 2020. [📄 Abstract] [✏️ Paper]
김건형, 장영수, 이종민, and 김기응: 몬테 카를로 목표를 위한 분산 감소 방법. 한국통신학회 하계종합학술발표회. 2019. [📄 Abstract] [✏️ Paper]
이종민, 김건형, and 김기응: 연속 행동공간에서의 몬테-카를로 트리 탐색에 관한 연구. 한국통신학회 하계종합학술발표회. 2019. [📄 Abstract] [✏️ Paper]
Nianyin Zeng, Zidong Wang, Hong Zhang, Kee-Eung Kim, Yurong Li, and Xiaohui Liu: An Improved Particle Filter With a Novel Hybrid Proposal Distribution for Quantitative Analysis of Gold Immunochromatographic Strips. IEEE Transactions on Nanotechnology, 18:819-829. 2019. [📄 Abstract] [✏️ Paper]
Yung-Kyun Noh, Ji Young Park, Byoung Geol Choi, Kee-Eung Kim, and Seung-Woon Rha: A Machine Learning-Based Approach for the Prediction of Acute Coronary Syndrome Requiring Revascularization. Journal of Medical Systems. 2019. [📄 Abstract] [✏️ Paper]
Youngsoo Jang, Jongmin Lee, and Kee-Eung Kim: Bayes-Adaptive Monte-Carlo Planning and Learning for Goal-Oriented Dialogues. Neural Information Processing Systems (NeurIPS) Conversational AI workshop. 2019. [📄 Abstract] [✏️ Paper]
Geon-Hyeong Kim, Youngsoo Jang, Jongmin Lee, Wonseok Jeon, Hongseok Yang, and Kee-Eung Kim: Trust Region Sequential Variational Inference. Proceedings of Asian Conference on Machine Learning (ACML). 2019. [📄 Abstract] [✏️ Paper]
Youngsoo Jang*, Jongmin Lee*, Jaeyoung Park*, Kyeng-Hun Lee, Pierre Lison, and Kee-Eung Kim: PyOpenDial: A Python-based Domain-Independent Toolkit for Developing Spoken Dialogue Systems with Probabilistic Rules. Proceedings of Empirical Methods in Natural Language Processing (EMNLP) System Demonstrations. 2019. [📄 Abstract] [✏️ Paper]
강민구 and 김기응: 강화학습을 이용한 초고속비행체 제어기 학습. 한국군사과학기술학회 종합학술대회. 2019. [📄 Abstract] [✏️ Paper]
Kanghoon Lee, Geon-Hyeong Kim, Pedro Ortega, Daniel D. Lee, and Kee-Eung Kim: Bayesian optimistic Kullback-Leibler exploration. Machine Learning Journal (MLJ), 108. 2019. [📄 Abstract] [🔗 Link]
김건형, 장영수, 이종민, and 김기응: 모델 기반 베이지안 강화학습의 연속된 도메인으로의 확장에 대한 연구. 한국통신학회 하계종합학술발표회 논문집. 2018. [📄 Abstract] [🔗 Link]
Wonseok Jeon, Seokin Seo, and Kee-Eung Kim: A Bayesian Approach to Generative Adversarial Imitation Learning. Advances in Neural Information Processing Systems (NeurIPS). 2018. Spotlight [📄 Abstract] [✏️ Paper]
Jongmin Lee, Geon-Hyeong Kim, Pascal Poupart, and Kee-Eung Kim: Monte-Carlo Tree Search for Constrained POMDPs. Advances in Neural Information Processing Systems (NeurIPS). 2018. [📄 Abstract] [✏️ Paper]
Eun Sang Cha, Kee-Eung Kim, Stefano Longo, and Ankur Mehta: OP-CAS: Collision Avoidance with Overtaking Maneuvers. Proceedings of the IEEE Intelligent Transport Systems Conference (ITSC). 2018. [📄 Abstract] [✏️ Paper]
MinKu Kang and Kee-Eung Kim: Simulated Physics for High Speed Aerial Systems. Proceedings of International Conference on Control, Automation and Systems (ICCAS). 2018. [📄 Abstract] [✏️ Paper]
Jongmin Lee, Geon-Hyeong Kim, Pascal Poupart, and Kee-Eung Kim: Monte-Carlo Tree Search for Constrained MDPs. ICML/IJCAI/AAMAS Workshop on Planning and Learning (PAL). 2018. [📄 Abstract] [✏️ Paper]
Youngsoo Jang, Jiyeon Ham, Byung-Jun Lee, and Kee-Eung Kim: Cross-language Neural Dialog State Tracker for Large Ontologies using Hierarchical Attention. IEEE/ACM Transactions on Audio, Speech, and Language Processing (TASLP). 2018. [📄 Abstract] [🔗 Link]
Jiyeon Ham, Soohyun Lim, Kyeng-Hun Lee, and Kee-Eung Kim: Extensions to hybrid code networks for FAIR dialog dataset. Computer Speech and Language:12. 2018. [📄 Abstract] [🔗 Link]
Jang Won Bae, Junseok Lee, Do-Hyung Kim, Kanghoon Lee, Jongmin Lee, Kee-Eung Kim, and Il-Chul Moon: Layered Behavior Modeling via Combining Descriptive and Prescriptive Approaches: a Case Study of Infantry Company Engagement. IEEE Transactions on System, Man, and Cybernetics: Systems. 2018. [📄 Abstract] [🔗 Link]
Kee-Eung Kim and Hyun-Soo Park: Imitation Learning via Kernel Mean Embedding. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI). 2018. [📄 Abstract] [✏️ Paper] [🧑💻 Code]
Jiyeon Ham, Soohyun Lim, and Kee-Eung Kim: Extended Hybrid Code Networks for DSTC6 FAIR Dialog Dataset. Dialog System Technology Challenges 6 Workshop. 2017. [📄 Abstract] [✏️ Paper]
Yung-Kyun Noh, Masashi Sugiyama, Kee-Eung Kim, Frank Park, and Daniel Lee: Generative Local Metric Learning for Kernel Regression. Advances in Neural Information Processing Systems (NIPS). 2017. [📄 Abstract] [✏️ Paper]
Jang Won Bae, Bowon Nam, Kee-Eung Kim, Junseok Lee, and Il-Chul Moon: Hybrid Modeling and Simulation of Tactical Maneuvers in Computer Generated Force. Proceedings of the IEEE Conference on System, Man, and Cybernetics (SMC). 2017. [📄 Abstract] [✏️ Paper]
Jongmin Lee, Youngsoo Jang, Pascal Poupart, and Kee-Eung Kim: Constrained Bayesian Reinforcement Learning via Approximate Linear Programming. ECML-PKDD Workshop on Scaling-Up Reinforcement Learning (SURL). 2017. [📄 Abstract] [✏️ Paper]
이종민, 홍정표, 박재영, 이강훈, 김기응, 문일철, and 박재현: 대화력전 및 기계화 보병 시나리오를 통한 대규모 가상군의 POMDP 행동계획 및 학습 사례연구. 정보과학회 컴퓨팅의 실제 논문지, 23(6):343-349. 2017. [📄 Abstract] [✏️ Paper]
Jongmin Lee, Youngsoo Jang, Pascal Poupart, and Kee-Eung Kim: Constrained Bayesian Reinforcement Learning via Approximate Linear Programming. Proceedings of International Joint Conference on Artificial Intelligence (IJCAI). 2017. [📄 Abstract] [✏️ Paper]
Byung-Jun Lee, Jongmin Lee, and Kee-Eung Kim: Hierarchically-partitioned Gaussian Process Approximation. Proceedings of Artificial Intelligence and Statistics (AISTATS). 2017. [📄 Abstract] [✏️ Paper]
Youngsoo Jang, Jiyeon Ham, Byung-Jun Lee, Youngjae Chang, and Kee-Eung Kim: Neural Dialog State Tracker for Large Ontologies by Attention Mechanism. IEEE Workshop on Spoken Language Technology. 2016. [📄 Abstract] [✏️ Paper]
Daehyun Lee, Jongmin Lee, and Kee-Eung Kim: Multi-View Automatic Lip-Reading using Neural Network. ACCV 2016 Workshop on Multi-view Lip-reading Challenges. 2016. [📄 Abstract] [✏️ Paper]
홍정표, 이종민, 이강훈, 한상규, 김기응, 문일철, and 박재현: 대규모 가상군의 POMDP 행동계획 및 학습 사례연구. 한국정보과학회 하계학술발표회 논문집. 2016. [📄 Abstract] [✏️ Paper]
홍택규, 김건형, 이병준, and 김기응: Multi-armed Bandit을 이용한 요격 무장 할당 문제의 확률적인 접근. 한국정보과학회 하계학술발표회 논문집. 2016. [📄 Abstract] [✏️ Paper]
Teakgyu Hong, Jongmin Lee, Kee-Eung Kim, Pedro A. Ortega, and Daniel Lee: Bayesian Reinforcement Learning with Behavioral Feedback. Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), pp. 1571-1577. 2016. [📄 Abstract] [🔗 Link]
Byung-Jun Lee and Kee-Eung Kim: Dialog History Construction with Long-Short Term Memory for Robust Generative Dialog State Tracking. Dialogue & Discourse 7(3). 2016. [📄 Abstract] [✏️ Paper]
Yeganeh Mashayekh Hayeri, Kee-Eung Kim, and Daniel D. Lee: An Inverse Reinforcement Learning Approach to Car Following Behaviors. TRB 95th Annual Meeting Compendium of Papers, Transportation Research Board. 2016. [📄 Abstract] [🔗 Link]
홍택규, 이병준, 김건형, and 김기응: 계층형 모델링을 통한 순차적 무장 할당 문제의 효과적인 접근. 한국정보과학회 동계학술발표회 논문집. 2015. [📄 Abstract] [🔗 Link]
Pedro Ortega, Kee-Eung Kim, and Daniel Lee: Reactive bandits with attitude. Proceedings of Artificial Intelligence and Statistics (AISTATS). 2015. [📄 Abstract] [✏️ Paper]
Jaedeug Choi and Kee-Eung Kim: Hierarchical Bayesian Inverse Reinforcement Learning. IEEE Transactions on Cybernetics, 45(4). 2015. [📄 Abstract] [✏️ Paper]
Pascal Poupart, Aarti Malhotra, Pei Pei, Kee-Eung Kim, Bongseok Goh, and Michael Bowling: Approximate Linear Programming for Constrained Partially Observable Markov Decision Processes. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI). 2015. [📄 Abstract] [✏️ Paper]
Hyeoneun Kim, Woosang Lim, Kanghoon Lee, Yung-Kyun Noh, and Kee-Eung Kim: Reward Shaping for Model-Based Bayesian Reinforcement Learning. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI). 2015. [📄 Abstract] [✏️ Paper]
Kanghoon Lee and Kee-Eung Kim: Tighter Value Function Bounds for Bayesian Reinforcement Learning. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI). 2015. [📄 Abstract] [✏️ Paper]
Byung-Jun Lee, Woosang Lim, and Kee-Eung Kim: Optimizing Generative Dialog State Tracker via Cascading Gradient Descent. Proceedings of the SIGDIAL, pp. 273-281. 2014. [📄 Abstract] [✏️ Paper]
Hyeoneun Kim, Bongseok Goh, Bowon Nam, Kanghoon Lee, Jeong Hee Hong, Il Chul Moon, and Kee-Eung Kim: Multi-Level Hybrid Behavior Model of Computer Generated Forces. Proceedings of the AAMAS Workshop on Agents, Virtual Societies and Analytics. 2014. [📄 Abstract] [✏️ Paper]
홍택규, 고봉석, and 김기응: 키-시퀀스 예측을 통한 가변형 소프트 키보드 - 안드로이드 플랫폼 적용 사례 연구. 한국컴퓨터종합학술대회 논문집, pp. 1767-1769. 2014. [📄 Abstract] [✏️ Paper]
배장원, 이강훈, 김현은, 이준석, 고봉석, 남보원, 문일철, 김기응, and 박재현: POMDP-DEVS를 활용한 전투 개체 모델링. 대한산업공학회지, 39(6):498-516. 2013. [📄 Abstract] [✏️ Paper]
임희진, 최재득, 석재현, and 김기응: 추천시스템을 위한 베이지안 협력-경쟁 필터링. 한국컴퓨터종합학술대회 논문집, pp. 1496-1498. 2013. [📄 Abstract] [✏️ Paper]
Daejoong Kim, Jaedeug Choi, Kee-Eung Kim, Jungsu Lee, and Jinho Sohn: Engineering Statistical Dialog State Trackers: A Case Study on DSTC. Department of Computer Science, KAIST, Technical Report(CS-TR-2013-379). 2013. [📄 Abstract] [✏️ Paper]
Daejoong Kim, Jaedeug Choi, Kee-Eung Kim, Jungsu Lee, and Jinho Sohn: Engineering Statistical Dialog State Trackers: A Case Study on DSTC. Proceedings of the SIGDIAL 2013 Conference, pp. 462-466. 2013. [📄 Abstract] [✏️ Paper]
Jaedeug Choi and Kee-Eung Kim: Bayesian Nonparametric Feature Construction for Inverse Reinforcement Learning. Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI). 2013. [📄 Abstract] [✏️ Paper] [🧑💻 Code]
Jaedeug Choi and Kee-Eung Kim: Nonparametric Bayesian Inverse Reinforcement Learning for Multiple Reward Functions. Advances in Neural Information Processing Systems (NIPS). 2012. [📄 Abstract] [✏️ Paper] [🧑💻 Code]
Dongho Kim, Kee-Eung Kim, and Pascal Poupart: Cost-Sensitive Exploration in Bayesian Reinforcement Learning. Advances in Neural Information Processing Systems (NIPS). 2012. [📄 Abstract] [✏️ Paper]
이강훈, 임희진, and 김기응: A POMDP Approach to Optimizing P300 Speller BCI Paradigm. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 20(4). 2012. [📄 Abstract] [✏️ Paper] [🔗 Link]
이강훈, 임희진, and 김기응: Factored POMDP를 이용한 가상군의 자율행위 모델링 사례연구. 한국컴퓨터종합학술대회 논문집, vol. 39(1B). 2012. [📄 Abstract] [✏️ Paper]
Byung Kon Kang and Kee-Eung Kim: Exploiting Symmetries for Single and Multi-Agent Partially Observable Stochastic Domains. Artificial Intelligence, 182-183:32-57. 2012. [📄 Abstract] [✏️ Paper]
김동호, 이재송, 최재득, and 김기응: 복수 무인기를 위한 POMDP 기반 동적 임무 할당 및 정찰 임무 최적화 기법. 정보과학회 논문지: 소프트웨어 및 응용, 39(6). 2012. [📄 Abstract] [✏️ Paper]
Jaedeug Choi and Kee-Eung Kim: MAP Inference for Bayesian Inverse Reinforcement Learning. Advances in Neural Information Processing Systems (NIPS). 2011. [📄 Abstract] [✏️ Paper]
Jaeyoung Park, Kee-Eung Kim, and Yoon-Kyu Song: A POMDP-based Optimal Control of P300-based Brain-Computer Interfaces. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI) NECTAR Track. 2011. [📄 Abstract] [✏️ Paper]
Dongho Kim, Jaesong Lee, Kee-Eung Kim, and Pascal Poupart: Point-Based Value Iteration for Constrained POMDPs. Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI). 2011. [📄 Abstract] [✏️ Paper]
Dongho Kim, Jaesong Lee, Kee-Eung Kim, and Pascal Poupart: Point-Based Value Iteration for Constrained POMDPs. Proceedings of the IJCAI Workshop on Decision Making in Partially Observable, Uncertain Worlds: Exploring Insights from Multiple Communities. 2011. [📄 Abstract] [✏️ Paper]
Eunsoo Oh and Kee-Eung Kim: A Geometric Traversal Algorithm for Reward-Uncertain MDPs. Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI). 2011. [📄 Abstract] [✏️ Paper]
김동호, 이재송, 김기응, and 파스칼 푸파르: 제약을 갖는 POMDP를 위한 점-기반 가치 반복 알고리즘. 한국컴퓨터종합학술대회 논문집, vol. 38(1A). 2011. 최우수 논문상 [📄 Abstract] [✏️ Paper]
Pascal Poupart, Kee-Eung Kim, and Dongho Kim: Closing the Gap: Towards Provably Optimal POMDP Solutions. Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS). 2011. [📄 Abstract] [✏️ Paper]
Dongho Kim, Jin Hyung Kim, and Kee-Eung Kim: Robust Performance Evaluation of POMDP-Based Dialogue Systems. IEEE Transactions on Audio, Speech, and Language Processing (TASLP), 19(4). 2011. [📄 Abstract] [✏️ Paper] [🔗 Link]
Jaedeug Choi and Kee-Eung Kim: Inverse Reinforcement Learning in Partially Observable Environments. Journal of Machine Learning Research (JMLR), 12. 2011. [📄 Abstract] [✏️ Paper] [🧑💻 Code]
김동호 and 김기응: 부분관찰 마코프 의사결정과정을 이용한 지능형 에이전트 구현. 한국정보과학회지, 29(2). 2011. [📄 Abstract] [✏️ Paper]
Wonjun Lee, Sunjun Kim, Younkyung Lim, Alice Oh, Tekjin Nam, and Kee-Eung Kim: A Rapid Prototyping Method for Discovering User-Driven Opportunities for Personal Informatics. Proceedings of the International Conference on Virtual Systems and Multimedia (VSMM). 2010. Best Paper Award [📄 Abstract] [✏️ Paper]
Younkyung Lim, Alice Oh, Tekjin Nam, and Kee-Eung Kim: Personal Informatics for Discovering Human-Centered Lifecare System Opportunities. Proceedings of the ACM CHI Workshop on Know Thyself. 2010. [📄 Abstract] [✏️ Paper]
Jaeyoung Park, Kee-Eung Kim, and Sungho Jo: A POMDP Approach to P300-Based Brain-Computer Interfaces. Proceedings of the ICAPS POMDP Practitioners Workshop. 2010. [📄 Abstract] [✏️ Paper]
Youngwook Kim and Kee-Eung Kim: Point-Based Bounded Policy Iteration for Decentralized POMDPs. Proceedings of Pacific-Rim Conference on Artificial Intelligence (PRICAI) / Lecture Notes in Computer Science (LNCS) 6230. 2010. Best Poster Award [📄 Abstract] [🔗 Link]
Jaeyoung Park, Kee-Eung Kim, and Sungho Jo: A POMDP Approach to P300-Based Brain-Computer Interfaces. Proceedings of the ACM International Conference on Intelligent User Interfaces (IUI). 2010. [📄 Abstract] [✏️ Paper]
Jaedeug Choi and Kee-Eung Kim: Inverse Reinforcement Learning in Partially Observable Environments. Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI). 2009. [📄 Abstract] [✏️ Paper] [🧑💻 Code]
Dongho Kim, Hyeong Seop Sim, Kee-Eung Kim, Jin Hyung Kim, Hyunjeong Kim, and Joo Won Sung: Effects of User Modeling on POMDP-based Dialogue Systems. Proceedings of the Annual Conference of the International Speech Communication Association (INTERSPEECH). 2008. Best Student Paper Runner-up [📄 Abstract] [✏️ Paper]
Jae-Hyun Seok, Simon Levasseur, Kee-Eung Kim, and Jin Hyung Kim: Tracing Handwriting on Paper Document under Video Camera. Proceedings of the International Conference on Frontiers in Handwriting Recognition (ICFHR). 2008. [📄 Abstract] [✏️ Paper]
Hyeong Seop Sim, Kee-Eung Kim, Jin Hyung Kim, Du-Seong Chang, and Myoung-Wan Koo: Symbolic Heuristic Search Value Iteration for Factored POMDPs. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI). 2008. [📄 Abstract] [✏️ Paper]
Kee-Eung Kim: Exploiting Symmetries in POMDPs for Point-Based Algorithms. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI). 2008. [📄 Abstract] [✏️ Paper]
Jihoon Kim, Taik Heon Rhee, Kee-Eung Kim, and Jin Hyung Kim: Place Recognition Using Multiple Wearable Cameras. Proc. of 4th International Symposium on Ubiquitous Computing Systems (UCS) / Lecture Notes in Computer Science (LNCS) 4836. 2007. [📄 Abstract] [✏️ Paper]
Jihoon Kim, Taik Heon Rhee, Kee-Eung Kim, and Jin Hyung Kim: Signboard Recognition by Consistency Checking of Local Features. 2nd Korea-Japan Joint Workshop on Pattern Recognition (KJPR). 2007. [📄 Abstract] [✏️ Paper]
Kee-Eung Kim, Wook Chang, Sung-Jung Cho, Junghyun Shim, Hyunjeong Lee, Joonah Park, Youngbeom Lee, and Sangryoung Kim: Hand Grip Pattern Recognition for Mobile User Interfaces. Proceedings of the Innovative Applications of Artificial Intelligence Conference (IAAI). 2006. [📄 Abstract] [✏️ Paper]
Wook Chang, Kee-Eung Kim, Hyunjeong Lee, Joon Kee Cho, Byung Seok Soh, Jung Hyun Shim, Gyunghye Yang, Sung-Jung Cho, and Joonah Park: Recognition of Grip-Patterns by using Capacitive Touch Sensors. Proceedings of the IEEE International Symposium on Industrial Electronics (ISIE). 2006. [📄 Abstract] [✏️ Paper]
Kee-Eung Kim, Taeseo Park, Min-Kyu Park, Youngbeom Lee, Yunbae Kim, and Sangryoung Kim: Adaptive Event Clustering for Personalized Photo Browsing. 한국 HCI 학술대회 논문집 (Proceedings of Korean HCI Conference). 2006. [📄 Abstract] [✏️ Paper]
Wook Chang, Kee-Eung Kim, Hyunjeong Lee, Joonki Cho, Byeongsuk Soh, Junghyun Shim, Kyunghye Yang, Sung-Jung Cho, and Junah Park: Designing Mobile User Interfaces Using Hand Grip Recognition. 한국 HCI 학술대회 논문집 (Proceedings of Korean HCI Conference). 2006.
SeongHwan Cho and Kee-Eung Kim: Variable Bandwidth Allocation Scheme for Energy Efficient Wireless Sensor Network. Proceedings of the IEEE International Conference on Communications (ICC). 2005. [📄 Abstract] [✏️ Paper]
Wook Chang, Juna Park, Kee-Eung Kim, Sung-Jung Cho, Hyun-Jung Lee, and Junghyun Shim: 접촉 센서를 이용한 사용자 인터페이스 설계 (Designing a Touch-based User Interface System for Handheld Devices). 한국 HCI 학술대회 논문집 (Proceedings of Korean HCI Conference). 2005. [📄 Abstract] [✏️ Paper]
Kee-Eung Kim and Thomas Dean: Solving Factored MDPs Using Non-Homogeneous Partitions. Artificial Intelligence, 147(1-2). 2003.
Kee-Eung Kim and Thomas Dean: Solving Factored MDPs with Large Action Space Using Algebraic Decision Diagrams. Proceedings of Pacific-Rim Conference on Artificial Intelligence (PRICAI) / Lecture Notes in Computer Science (LNCS) 2417. 2002.
Kee-Eung Kim and Thomas Dean: Solving Factored MDPs via Non-homogeneous Partitioning. Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence (IJCAI). 2001.
Nicolas Meuleau, Leonid Peshkin, and Kee-Eung Kim: Exploration in Gradient-based Reinforcement Learning. MIT, AI Memo(2001-003). 2001.
Kee-Eung Kim, Thomas Dean, and Nicolas Meuleau: Approximate Solutions to Factored Markov Decision Processes via Greedy Search in the Space of Finite State Controllers. Proceedings of the Fifth International Conference on Artificial Intelligence in Planning and Scheduling (AIPS). 2000.
Leonid Peshkin, Kee-Eung Kim, Nicolas Meuleau, and Leslie Pack Kaelbling: Learning to Cooperate via Policy Search. Proceedings of the Sixteenth Conference on Uncertainty in Artificial Intelligence (UAI). 2000.
Kee-Eung Kim, Thomas Dean, and Samuel Hazlehurst: Linear Algebra in Very High-Dimension Vector Spaces With an Application to Solving Markov Decision Processes. Neural Computing Surveys, 3. 2000.
Kee-Eung Kim, Thomas Dean, and Samuel Hazlehurst: Linear Algebra in Very High-Dimension Vector Spaces: Algorithms and Data Structures for Implementing Exact and Approximate Solution Methods. Department of Computer Science, Brown University, Technical Report(CS-00-02). 2000.
Thomas Dean, Kee-Eung Kim, and Samuel Hazlehurst: Linear Algebra in Very High-Dimension Vector Spaces With an Application to Solving Markov Decision Processes. Proceedings of IJCAI-99 Workshop on Statistical Machine Learning for Large-Scale Optimization. 1999.
Nicolas Meuleau, Leonid Peshkin, Kee-Eung Kim, and Leslie Pack Kaelbling: Learning Finite-State Controllers for Partially Observable Environments. Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence (UAI). 1999.
Nicolas Meuleau, Kee-Eung Kim, Leslie Pack Kaelbling, and Anthony R. Cassandra: Solving POMDPs by Searching the Space of Finite Policies. Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence (UAI). 1999.
Nicolas Meuleau, Milos Hauskrecht, Kee-Eung Kim, Leonid Peshkin, Leslie Pack Kaelbling, Thomas Dean, and Craig Boutilier: Solving Very Large Weakly Coupled Markov Decision Processes. Proceedings of the Fifteenth National Conference on Artificial Intelligence (AAAI). 1998.
Thomas Dean, Kee-Eung Kim, and Robert Givan: Solving Planning Problems with Large State and Action Spaces. Proceedings of the Fourth International Conference on Artificial Intelligence Planning Systems (AIPS). 1998.