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Kyoungseok Jang
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Year
Tighter PAC-Bayes bounds through coin-betting
K Jang, KS Jun, I Kuzborskij, F Orabona
The Thirty Sixth Annual Conference on Learning Theory, 2240-2264, 2023
382023
Popart: Efficient sparse regression and experimental design for optimal sparse linear bandits
K Jang, C Zhang, KS Jun
Advances in Neural Information Processing Systems 35, 2102-2114, 2022
242022
Improved regret bounds of bilinear bandits using action space analysis
K Jang, KS Jun, SY Yun, W Kang
International Conference on Machine Learning, 4744-4754, 2021
142021
Better-than-KL PAC-Bayes bounds
I Kuzborskij, KS Jun, Y Wu, K Jang, F Orabona
The Thirty Seventh Annual Conference on Learning Theory, 3325-3352, 2024
82024
Efficient low-rank matrix estimation, experimental design, and arm-set-dependent low-rank bandits
K Jang, C Zhang, KS Jun
arXiv preprint arXiv:2402.11156, 2024
62024
Fixed confidence best arm identification in the Bayesian setting
K Jang, J Komiyama, K Yamazaki
Advances in Neural Information Processing Systems 37, 17789-17829, 2024
22024
Sparsity-agnostic linear bandits with adaptive adversaries
T Jin, K Jang, N Cesa-Bianchi
Advances in Neural Information Processing Systems 37, 42015-42047, 2024
12024
Online Linear Regression with Paid Stochastic Features
N Merlis, K Jang, N Cesa-Bianchi
arXiv preprint arXiv:2511.08073, 2025
2025
Rate-optimal Design for Anytime Best Arm Identification
J Komiyama, K Jang, J Honda
arXiv preprint arXiv:2510.23199, 2025
2025
GL-LowPopArt: A Nearly Instance-Wise Minimax Estimator for Generalized Low-Rank Trace Regression
J Lee, K Jang, KS Jun, M Vojnović, SY Yun
arXiv preprint arXiv:2506.03074, 2025
2025
Sparsity-agnostic linear bandits with adaptive adversaries.
J Tianyuan, K Jang, N Cesa-Bianchi
< bound method Organization. get_name_with_acronym of< Organization: EU Open …, 2024
2024
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Articles 1–11