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Online Kernel Selection with Multiple Bandit Feedbacks in Random Feature Space.

, and . KSEM (2), volume 11062 of Lecture Notes in Computer Science, page 301-312. Springer, (2018)

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Improved Regret Bounds for Online Kernel Selection Under Bandit Feedback., and . ECML/PKDD (4), volume 13716 of Lecture Notes in Computer Science, page 333-348. Springer, (2022)An Online Kernel Selection Wrapper via Multi-Armed Bandit Model., and . ICPR, page 1307-1312. IEEE Computer Society, (2018)Online Kernel Selection via Grouped Adversarial Bandit Model., and . ICTAI, page 682-689. IEEE, (2019)A New Learning Algorithm with General Loss for Neural Networks with Random Weights., , and . ICTAI, page 1-5. IEEE, (2020)Nearly Optimal Algorithms with Sublinear Computational Complexity for Online Kernel Regression., and . ICML, volume 202 of Proceedings of Machine Learning Research, page 19743-19766. PMLR, (2023)Ahpatron: A New Budgeted Online Kernel Learning Machine with Tighter Mistake Bound., , , , and . AAAI, page 13782-13789. AAAI Press, (2024)Online Kernel Selection with Multiple Bandit Feedbacks in Random Feature Space., and . KSEM (2), volume 11062 of Lecture Notes in Computer Science, page 301-312. Springer, (2018)Worst-case regret analysis of computationally budgeted online kernel selection., and . Mach. Learn., 111 (3): 937-976 (2022)High-Probability Kernel Alignment Regret Bounds for Online Kernel Selection., and . ECML/PKDD (1), volume 12975 of Lecture Notes in Computer Science, page 67-83. Springer, (2021)Improved Kernel Alignment Regret Bound for Online Kernel Learning., and . AAAI, page 8597-8604. AAAI Press, (2023)