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Non-convex learning via Stochastic Gradient Langevin Dynamics: a nonasymptotic analysis.

, , and . COLT, volume 65 of Proceedings of Machine Learning Research, page 1674-1703. PMLR, (2017)

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High-Probability Regret Bounds for Bandit Online Linear Optimization., , , , , and . COLT, page 335-342. Omnipress, (2008)Information-Based Complexity, Feedback and Dynamics in Convex Programming., and . IEEE Trans. Inf. Theory, 57 (10): 7036-7056 (2011)Online discovery of similarity mappings., , and . ICML, volume 227 of ACM International Conference Proceeding Series, page 767-774. ACM, (2007)On the Risk of Minimum-Norm Interpolants and Restricted Lower Isometry of Kernels., , and . CoRR, (2019)Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization., , and . ICML, icml.cc / Omnipress, (2012)BISTRO: An Efficient Relaxation-Based Method for Contextual Bandits., and . ICML, volume 48 of JMLR Workshop and Conference Proceedings, page 1977-1985. JMLR.org, (2016)On Equivalence of Martingale Tail Bounds and Deterministic Regret Inequalities., and . COLT, volume 65 of Proceedings of Machine Learning Research, page 1704-1722. PMLR, (2017)ResNet., , , , , , , , , and 1 other author(s). Computer-Aided Analysis of Gastrointestinal Videos, Springer, (2021)Game-theoretic timing analysis., and . ICCAD, page 575-582. IEEE Computer Society, (2008)Online Estimation via Offline Estimation: An Information-Theoretic Framework., , , and . CoRR, (2024)