Email: dlqudwns2002@gmail.com
Just got a Ph.D. in Machine Learning, Reinforcement Learning, Offline Reinforcement Learning. (2015~2021, advised by Prof. Kee-Eung Kim, got best thesis award as well!)
Currently working as an applied scientist in Gauss Labs Inc.
Jongmin Lee*, Wonseok Jeon*, Byung-Jun Lee, Joelle Pineau and Kee-Eung Kim, "OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation", in International Conference on Machine Learning (ICML), 2021 (*: equally contributed)
Byung-Jun Lee, Jongmin Lee and Kee-Eung Kim, "Representation balancing offline model-based reinforcement learning", in International Conference on Learning Representations (ICLR), 2021
Deunsol Yoon*, Sunghoon Hong*, Byung-Jun Lee and Kee-Eung Kim, "Winning the L2RPN challenge: power grid management via semi-Markov afterstate actor-critic", in International Conference on Learning Representations (ICLR), 2021 (*: equally contributed).
Jongmin Lee, Byung-Jun Lee and Kee-Eung Kim, "Reinforcement learning for control with multiple frequencies", in Thirty-Fourth Annual Conference on Neural Information Processing Systems (NeurlPS), 2020
Byung-Jun Lee*, Jongmin Lee*, Peter Vrancx, Dongho Kim and Kee-Eung Kim, "Batch reinforcement learning with hyperparameter gradients", in International Conference on Machine Learning (ICML), 2020 (*: equally contributed)
Byung-Jun Lee, Seunghoon Hong and Kee-Eung Kim, "Residual neural processes", in AAAI conference on Artificial Intelligence (AAAI), 2020
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
Byung-Jun Lee, Jongmin Lee and Kee-Eung Kim, "Hierarchically-partitioned Gaussian process approximation", in International Conference on 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 Spoken Language Technology Workship (SLT), 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 (D&D), 2016
Byung-Jun Lee and Kee-Eung Kim, "Optimizing Bayesian filtering model for statistical dialog state tracking", Master thesis, 2015
Byung-Jun Lee, Woosang Lim, Daejoong Kim and Kee-Eung Kim, "Optimizing generative dialog state tracker via cascading gradient descent", in Proceedings of the 15th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL), 2014
2020. 12. - Current. Applied scientist, Gauss Labs Inc.
2018. 01. - 2018. 07. Machine learning research intern, PROWLER.io (Current Secondmind)
Learning to Run a Power Network Challenge (L2RPN) 2020 WCCI (1st place), 2020
Naver Ph.D. Fellowship, Naver, 2017