Papers

(C: peer-reviewed conference, J: peer-reviewed journal, *: equal contributions)

2024

[C15] Offline Imitation Learning by Controlling the Effective Planning Horizon
Hee-Jun Ahn*, Seong-Woong Lee*, Byung-Jun Lee
International Conference on Pattern Recognition and Artificial Intelligence (ICPRAI), 2024

[C14] Relaxed Stationary Distribution Correction Estimation for Improved Offline Policy Optimization
Woo-Sung Kim, Dong-Hyeon Ki, Byung-Jun Lee
Annual AAAI Conference on Artificial Intelligence (AAAI), 2024 🎉Oral🎉

[J3] MARS: Multi-Agent Reinforcement Learning for Spatial-Spectral and Temporal Feature Selection in EEG-based BCI
Dong-Hee Shin, Young-Han Son, Jun-Mo Kim, Hee-Jun Ahn, Jun-Ho Seo, Chang-Hoon Ji, Ji-Wung Han, Byung-Jun Lee, Dong-Ok Won, and Tae-Eui Kam
IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2024

2023

[C13] Quantifying Information of Tokens for Simple and Flexible Simultaneous Machine Translation
DongHyun Lee, Minkyung Park, Byung-Jun Lee
Conference on Computational Natural Language Learning (CoNLL), 2023

[C12] Improving Neural Machine Translation with Offline Evaluations
Minkyung Park, Byung-Jun Lee
International Joint Conference on Natural Language Processing (IJCNLP), 2023

[C11] Adaptive Online Time-Series Prediction for Virtual Metrology in Semiconductor Manufacturing
Simon Zabrocki, Pil Sung Jo, Chan Park, Dongkyun Yim, Sunghee Yun, Byung-Jun Lee
Advanced Semiconductor Manufacturing Conference (ASMC), 2023

2022

[C10] Local Metric Learning for Off-Policy Evaluation in Contextual Bandits with Continuous Actions
Haanvid Lee, Jongmin Lee, Yunseon Choi, Wonseok Jeon, Byung-Jun Lee, Yung-Kyun Noh, Kee-Eung Kim
Annual Conference on Neural Information Processing Systems (NeurlPS), 2022

~ 2021

[C9] OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation
Jongmin Lee*, Wonseok Jeon*, Byung-Jun Lee, Joelle Pineau and Kee-Eung Kim
International Conference on Machine Learning (ICML), 2021

[C8] Representation balancing offline model-based reinforcement learning
Byung-Jun Lee, Jongmin Lee and Kee-Eung Kim
International Conference on Learning Representations (ICLR), 2021

[C7] Winning the L2RPN challenge: power grid management via semi-Markov afterstate actor-critic
Deunsol Yoon*, Sunghoon Hong*, Byung-Jun Lee and Kee-Eung Kim
International Conference on Learning Representations (ICLR), 2021
Spotlight Presentation

[C6] Reinforcement learning for control with multiple frequencies
Jongmin Lee, Byung-Jun Lee and Kee-Eung Kim
Annual Conference on Neural Information Processing Systems (NeurlPS), 2020

[C5] Batch reinforcement learning with hyperparameter gradients
Byung-Jun Lee*, Jongmin Lee*, Peter Vrancx, Dongho Kim and Kee-Eung Kim
International Conference on Machine Learning (ICML), 2020

[C4] Residual neural processes
Byung-Jun Lee, Seunghoon Hong and Kee-Eung Kim
AAAI conference on Artificial Intelligence (AAAI), 2020

[J2] Cross-language neural dialog state tracker for large ontologies using hierarchical attention
Youngsoo Jang, Jiyeon Ham, Byung-Jun Lee and Kee-Eung Kim
IEEE/ACM Transactions on Audio, Speech, and Language Processing (TASLP), 2018

[C3] Hierarchically-partitioned Gaussian process approximation
Byung-Jun Lee, Jongmin Lee and Kee-Eung Kim
International Conference on Artificial Intelligence and Statistics (AISTATS), 2017

[C2] Neural dialog state tracker for large ontologies by attention mechanism
Youngsoo Jang, Jiyeon Ham, Byung-Jun Lee, Youngjae Chang and Kee-Eung Kim
IEEE Spoken Language Technology Workship (SLT), 2016

[J1] Dialog history construction with long-short term memory for robust generative dialog state tracking
Byung-Jun Lee and Kee-Eung Kim
Dialogue & Discourse (D&D), 2016

[C1] Optimizing generative dialog state tracker via cascading gradient descent
Byung-Jun Lee, Woosang Lim, Daejoong Kim and Kee-Eung Kim
Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL), 2014