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Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization.

, , , and . AISTATS, volume 151 of Proceedings of Machine Learning Research, page 8715-8737. PMLR, (2022)

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Combining Online Learning and Offline Learning for Contextual Bandits with Deficient Support., , , , and . CoRR, (2021)Calculus rules for proximal ε-subdifferentials and inexact proximity operators for weakly convex functions., , , and . ECC, page 1-8. IEEE, (2023)Calculus rules for proximal ε-subdifferentials and inexact proximity operators for weakly convex functions., , , and . CoRR, (2022)Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces., , , , and . NeurIPS, (2020)Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization., , , and . AISTATS, volume 151 of Proceedings of Machine Learning Research, page 8715-8737. PMLR, (2022)Expected Improvement for Contextual Bandits., , , , , and . NeurIPS, (2022)Neural-BO: A Black-box Optimization Algorithm using Deep Neural Networks., , and . CoRR, (2023)Regularity bounds for a Gevrey criterion in a kernel-based regularization of the Cauchy problem of elliptic equations., and . Appl. Math. Lett., (2017)On Sample Complexity of Offline Reinforcement Learning with Deep ReLU Networks in Besov Spaces., , , and . Trans. Mach. Learn. Res., (2022)On Finite-Sample Analysis of Offline Reinforcement Learning with Deep ReLU Networks., , , and . CoRR, (2021)