| Efficient frameworks for generalized low-rank matrix bandit problems Y Kang, CJ Hsieh, TCM Lee Advances in Neural Information Processing Systems 35, 19971-19983, 2022 | 15 | 2022 |
| Estimation of the number of endmembers via thresholding ridge ratio criterion X Zhu, Y Kang, J Liu IEEE Transactions on Geoscience and Remote Sensing 58 (1), 637-649, 2019 | 9 | 2019 |
| Adapting stepsizes by momentumized gradients improves optimization and generalization Y Wang, Y Kang, C Qin, H Wang, Y Xu, Y Zhang, Y Fu | 7 | 2021 |
| Robust lipschitz bandits to adversarial corruptions Y Kang, CJ Hsieh, TCM Lee Advances in Neural Information Processing Systems 36, 2024 | 5 | 2024 |
| Syndicated bandits: A framework for auto tuning hyper-parameters in contextual bandit algorithms Q Ding, Y Kang, YW Liu, TCM Lee, CJ Hsieh, J Sharpnack Advances in Neural Information Processing Systems 35, 1170-1181, 2022 | 5 | 2022 |
| Rethinking Adam: A twofold exponential moving average approach Y Wang, Y Kang, C Qin, H Wang, Y Xu, Y Zhang, Y Fu arXiv preprint arXiv:2106.11514, 2021 | 5 | 2021 |
| Online Continuous Hyperparameter Optimization for Generalized Linear Contextual Bandits Y Kang, CJ Hsieh, T Lee Transactions on Machine Learning Research, 2024 | 2* | 2024 |
| Low-rank Matrix Bandits with Heavy-tailed Rewards Y Kang, CJ Hsieh, T Lee arXiv preprint arXiv:2404.17709, 2024 | | 2024 |
| Efficient Frameworks for Generalized Low-Rank Matrix Bandit Problems Y Kang, CJ Hsieh, T Lee arXiv preprint at arXiv:2401.07298, 2024 | | 2024 |
| Momentum is All You Need for Data-Driven Adaptive Optimization Y Wang, Y Kang, C Qin, H Wang, Y Xu, Y Zhang, Y Fu 2023 IEEE International Conference on Data Mining (ICDM), 1385-1390, 2023 | | 2023 |
| Dynamic Continuous Hyperparameter Tuning for Generalized Linear Contextual Bandits Y Kang, CJ Hsieh, T Lee | | 2023 |
| Momentum in Momentum for Adaptive Optimization Y Wang, Y Kang, C Qin, H Wang, Y Xu, Y Zhang, Y Fu | | 2022 |
