Official Publications
Fixed Confidence Best Arm Identification in the Bayesian Setting
Kyoungseok Jang, Junpei Komiyama, Kazutoshi Yamazaki
In Conference on Neural Information Processing Systems (NeurIPS), accepted, 2024 link
Sparsity-Agnostic Linear Bandits with Adaptive Adversaries
Tianyuan Jin, Kyoungseok Jang, Nicolò Cesa-Bianchi
In Conference on Neural Information Processing Systems (NeurIPS), accepted, 2024 link
Efficient Low-Rank Matrix Estimation, Experimental Design, and Arm-Set-Dependent Low-Rank Bandits
Kyoungseok Jang, Kwang-sung Jun, Chicheng Zhang
In International Conference on Machine Learning (ICML), accepted, 2024 link
Better-than-KL PAC-Bayes bounds
Ilja Kuzborskij, Kwang-Sung Jun, Yulian Wu, Kyoungseok Jang, Francesco Orabona
In Conference on Learning Theory (COLT), accepted, 2024 link
Tighter PAC-Bayes bound through Coin-Betting
Kyoungseok Jang, Kwang-Sung Jun, Ilja Kuzborskij, Francesco Orabona
In Conference on Learning Theory (COLT), accepted, 2023 link
PopArt: Efficient Sparse Regression and Experimental Design for Optimal Sparse Linear Bandits
Kyoungseok Jang, Chicheng Zhang, Kwang-Sung Jun
In Conference on Neural Information Processing Systems (NeurIPS), accepted, 2022 link
Improved Regret Bounds of Bilinear Bandits using Action Space Analysis.
Kyoungseok Jang, Kwang-Sung Jun, Se Young Yun, Wanmo Kang.
In International Conference on Machine Learning (ICML), accepted, 2021 link
Preprints
GL-LowPopArt: A Nearly Instance-Wise Minimax Estimator for (Adaptive) Generalized Linear Low-Rank Trace Regression
Junghyun Lee, Kyoungseok Jang, Kwang-Sung Jun, Milan Vojnovic, Se-Young Yun
Workshop paper
Fixed Confidence Best Arm Identification in the Bayesian Setting
Kyoungseok Jang, Junpei Komiyama, Kazutoshi Yamazaki
In the second RL theory workshop (co-located with COLT 2024), poster presentation, 2024
Improved Time-Uniform PAC-Bayes Bounds using Coin Betting
Kyoungseok Jang, Kwang-sung Jun, Ilja Kuzborskij, Francesco Orabona
In International Conference on Machine Learning (ICML) Workshop “PAC-Bayes meets Interactive Learning”, Contributed talk, 2023