Papers
This folder holds the following references to publications, sorted by year and author.
There are 71 references in this bibliography folder.
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.
Jongmin Lee, Youngsoo Jang, Pascal Poupart, and Kee-Eung Kim:
Constrained Bayesian Reinforcement Learning via Approximate Linear Programming
In: Proceedings of International Joint Conference on Artificial Intelligence (IJCAI).
2017.
Byung-Jun Lee, Jongmin Lee, and Kee-Eung Kim:
Hierarchically-partitioned Gaussian Process Approximation
In: Proceedings of Artificial Intelligence and Statistics (AISTATS).
2017.
Youngsoo Jang, Jiyeon Ham, Byung-Jun Lee, Youngjae Chang, and Kee-Eung Kim:
Neural Dialog State Tracker for Large Ontologies by Attention Mechanism
In: IEEE Workshop on Spoken Language Technology.
2016.
Daehyun Lee, Jongmin Lee, and Kee-Eung Kim:
Multi-View Automatic Lip-Reading using Neural Network
In: ACCV 2016 Workshop on Multi-view Lip-reading Challenges.
2016.
홍정표, 이종민, 이강훈, 한상규, 김기응, 문일철, and 박재현:
대규모 가상군의 POMDP 행동계획 및 학습 사례연구
In: 한국정보과학회 하계학술발표회 논문집.
2016.
홍택규, 김건형, 이병준, and 김기응:
Multi-armed Bandit을 이용한 요격 무장 할당 문제의 확률적인 접근
In: 한국정보과학회 하계학술발표회 논문집.
2016.
Teakgyu Hong, Jongmin Lee, Kee-Eung Kim, Pedro A. Ortega, and Daniel Lee:
Bayesian Reinforcement Learning with Behavioral Feedback
In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), pp. 1571-1577.
2016.
Byung-Jun Lee and Kee-Eung Kim:
Dialog History Construction with Long-Short Term Memory for Robust Generative Dialog State Tracking
In: Dialogue & Discourse 7(3).
2016.
Yeganeh Mashayekh Hayeri, Kee-Eung Kim, and Daniel D. Lee:
An Inverse Reinforcement Learning Approach to Car Following Behaviors
In: TRB 95th Annual Meeting Compendium of Papers, Transportation Research Board.
2016.
홍택규, 이병준, 김건형, and 김기응:
계층형 모델링을 통한 순차적 무장 할당 문제의 효과적인 접근
In: 한국정보과학회 동계학술발표회 논문집.
2015.
Pedro Ortega, Kee-Eung Kim, and Daniel Lee:
Reactive bandits with attitude
In: Proceedings of Artificial Intelligence and Statistics (AISTATS).
2015.
Jaedeug Choi and Kee-Eung Kim:
Hierarchical Bayesian Inverse Reinforcement Learning
IEEE Transactions on Cybernetics, 45(4).
2015.
Pascal Poupart, Aarti Malhotra, Pei Pei, Kee-Eung Kim, Bongseok Goh, and Michael Bowling:
Approximate Linear Programming for Constrained Partially Observable Markov Decision Processes
In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI).
2015.
Hyeoneun Kim, Woosang Lim, Kanghoon Lee, Yung-Kyun Noh, and Kee-Eung Kim:
Reward Shaping for Model-Based Bayesian Reinforcement Learning
In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI).
2015.
Kanghoon Lee and Kee-Eung Kim:
Tighter Value Function Bounds for Bayesian Reinforcement Learning
In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI).
2015.
Byung-Jun Lee, Woosang Lim, and Kee-Eung Kim:
Optimizing Generative Dialog State Tracker via Cascading Gradient Descent
In: Proceedings of the SIGDIAL 2014 Conference, pp. 273–281.
2014.
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
In: Proceedings of the AAMAS Workshop on Agents, Virtual Societies and Analytics.
2014.
홍택규, 고봉석, and 김기응:
키-시퀀스 예측을 통한 가변형 소프트 키보드 - 안드로이드 플랫폼 적용 사례 연구
In: 한국컴퓨터종합학술대회 논문집, pp. 1767-1769.
2014.
배장원, 이강훈, 김현은, 이준석, 고봉석, 남보원, 문일철, 김기응, and 박재현:
POMDP-DEVS를 활용한 전투 개체 모델링
대한산업공학회지, 39(6):498-516.
2013.
임희진, 최재득, 석재현, and 김기응:
추천시스템을 위한 베이지안 협력-경쟁 필터링
In: 한국컴퓨터종합학술대회 논문집, pp. 1496-1498.
2013.
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.
Daejoong Kim, Jaedeug Choi, Kee-Eung Kim, Jungsu Lee, and Jinho Sohn:
Engineering Statistical Dialog State Trackers: A Case Study on DSTC
In: Proceedings of the SIGDIAL 2013 Conference, pp. 462-466.
2013.
Jaedeug Choi and Kee-Eung Kim:
Bayesian Nonparametric Feature Construction for Inverse Reinforcement Learning
In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI).
2013.
Jaedeug Choi and Kee-Eung Kim:
Nonparametric Bayesian Inverse Reinforcement Learning for Multiple Reward Functions
In: Proceedings of Neural Information Processing Systems (NIPS).
2012.
