Van Der Hoeven, Dirk

15 publications

JMLR 2025 A Unified Analysis of Nonstochastic Delayed Feedback for Combinatorial Semi-Bandits, Linear Bandits, and MDPs Lukas Zierahn, Dirk van der Hoeven, Tal Lancewicki, Aviv Rosenberg, Nicolò Cesa-Bianchi

NeurIPS 2025 When Lower-Order Terms Dominate: Adaptive Expert Algorithms for Heavy-Tailed Losses Antoine Moulin, Emmanuel Esposito, Dirk van der Hoeven

ICML 2023 Delayed Bandits: When Do Intermediate Observations Help? Emmanuel Esposito, Saeed Masoudian, Hao Qiu, Dirk Van Der Hoeven, Nicolò Cesa-Bianchi, Yevgeny Seldin

ICML 2023 Trading-Off Payments and Accuracy in Online Classification with Paid Stochastic Experts Dirk Van Der Hoeven, Ciara Pike-Burke, Hao Qiu, Nicolò Cesa-Bianchi

AISTATS 2022 Nonstochastic Bandits and Experts with Arm-Dependent Delays Dirk Van Der Hoeven, Nicolò Cesa-Bianchi

NeurIPS 2022 A Near-Optimal Best-of-Both-Worlds Algorithm for Online Learning with Feedback Graphs Chloé Rouyer, Dirk van der Hoeven, Nicolò Cesa-Bianchi, Yevgeny Seldin

NeurIPS 2022 A Regret-Variance Trade-Off in Online Learning Dirk van der Hoeven, Nikita Zhivotovskiy, Nicolò Cesa-Bianchi

NeurIPS 2022 Learning on the Edge: Online Learning with Stochastic Feedback Graphs Emmanuel Esposito, Federico Fusco, Dirk van der Hoeven, Nicolò Cesa-Bianchi

NeurIPS 2021 Beyond Bandit Feedback in Online Multiclass Classification Dirk van der Hoeven, Federico Fusco, Nicolò Cesa-Bianchi

JMLR 2021 MetaGrad: Adaptation Using Multiple Learning Rates in Online Learning Tim van Erven, Wouter M. Koolen, Dirk van der Hoeven

NeurIPS 2020 Comparator-Adaptive Convex Bandits Dirk van der Hoeven, Ashok Cutkosky, Haipeng Luo

NeurIPS 2020 Exploiting the Surrogate Gap in Online Multiclass Classification Dirk van der Hoeven

COLT 2020 Open Problem: Fast and Optimal Online Portfolio Selection Tim Van Erven, Dirk Van der Hoeven, Wojciech Kotłowski, Wouter M. Koolen

NeurIPS 2019 User-Specified Local Differential Privacy in Unconstrained Adaptive Online Learning Dirk van der Hoeven

COLT 2018 The Many Faces of Exponential Weights in Online Learning Dirk van der Hoeven, Tim van Erven, Wojciech Kotlowski