| 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 | 38 | 2023 |
| 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 | 24 | 2022 |
| 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 | 14 | 2021 |
| 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 | 8 | 2024 |
| 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 | 6 | 2024 |
| 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 | 2 | 2024 |
| Sparsity-agnostic linear bandits with adaptive adversaries T Jin, K Jang, N Cesa-Bianchi Advances in Neural Information Processing Systems 37, 42015-42047, 2024 | 1 | 2024 |
| 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 |
Kwang-Sung JunThe University of ArizonaVerified email at cs.arizona.edu
