Dirk van der Hoeven

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 32

Top Topics

Multi Armed Bandits

Multiclass Classification

Convex Optimisation

Top Venues

Publications

Hidde Fokkema, Dirk van der Hoeven, Tor Lattimore, Jack J. Mayo
Online Newton Method for Bandit Convex Optimisation. CoRR (2024)
Hidde Fokkema, Dirk van der Hoeven, Tor Lattimore, Jack J. Mayo
Online Newton Method for Bandit Convex Optimisation Extended Abstract. COLT (2024)
Dirk van der Hoeven, Ciara Pike-Burke, Hao Qiu, Nicolò Cesa-Bianchi
Trading-Off Payments and Accuracy in Online Classification with Paid Stochastic Experts. ICML (2023)
Dirk van der Hoeven, Lukas Zierahn, Tal Lancewicki, Aviv Rosenberg, Nicolò Cesa-Bianchi
A Unified Analysis of Nonstochastic Delayed Feedback for Combinatorial Semi-Bandits, Linear Bandits, and MDPs. CoRR (2023)
Lukas Zierahn, Dirk van der Hoeven, Nicolò Cesa-Bianchi, Gergely Neu
Nonstochastic Contextual Combinatorial Bandits. AISTATS (2023)
Dirk van der Hoeven, Lukas Zierahn, Tal Lancewicki, Aviv Rosenberg, Nicolò Cesa-Bianchi
A Unified Analysis of Nonstochastic Delayed Feedback for Combinatorial Semi-Bandits, Linear Bandits, and MDPs. COLT (2023)
Dirk van der Hoeven, Nikita Zhivotovskiy, Nicolò Cesa-Bianchi
High-Probability Risk Bounds via Sequential Predictors. CoRR (2023)
Emmanuel Esposito, Saeed Masoudian, Hao Qiu, Dirk van der Hoeven, Nicolò Cesa-Bianchi, Yevgeny Seldin
Delayed Bandits: When Do Intermediate Observations Help? CoRR (2023)
Dirk van der Hoeven, Ciara Pike-Burke, Hao Qiu, Nicolò Cesa-Bianchi
Trading-Off Payments and Accuracy in Online Classification with Paid Stochastic Experts. CoRR (2023)
Emmanuel Esposito, Saeed Masoudian, Hao Qiu, Dirk van der Hoeven, Nicolò Cesa-Bianchi, Yevgeny Seldin
Delayed Bandits: When Do Intermediate Observations Help? ICML (2023)
Chloé Rouyer, Dirk van der Hoeven, Nicolò Cesa-Bianchi, Yevgeny Seldin
A Near-Optimal Best-of-Both-Worlds Algorithm for Online Learning with Feedback Graphs. NeurIPS (2022)
Dirk van der Hoeven, Nicolò Cesa-Bianchi
Nonstochastic Bandits and Experts with Arm-Dependent Delays. AISTATS (2022)
Emmanuel Esposito, Federico Fusco, Dirk van der Hoeven, Nicolò Cesa-Bianchi
Learning on the Edge: Online Learning with Stochastic Feedback Graphs. CoRR (2022)
Dirk van der Hoeven, Nikita Zhivotovskiy, Nicolò Cesa-Bianchi
A Regret-Variance Trade-Off in Online Learning. CoRR (2022)
Dirk van der Hoeven, Hédi Hadiji, Tim van Erven
Distributed Online Learning for Joint Regret with Communication Constraints. ALT (2022)
Emmanuel Esposito, Federico Fusco, Dirk van der Hoeven, Nicolò Cesa-Bianchi
Learning on the Edge: Online Learning with Stochastic Feedback Graphs. NeurIPS (2022)
Chloé Rouyer, Dirk van der Hoeven, Nicolò Cesa-Bianchi, Yevgeny Seldin
A Near-Optimal Best-of-Both-Worlds Algorithm for Online Learning with Feedback Graphs. CoRR (2022)
Dirk van der Hoeven, Nikita Zhivotovskiy, Nicolò Cesa-Bianchi
A Regret-Variance Trade-Off in Online Learning. NeurIPS (2022)
Dirk van der Hoeven, Nicolò Cesa-Bianchi
Nonstochastic Bandits and Experts with Arm-Dependent Delays. CoRR (2021)
Tim van Erven, Wouter M. Koolen, Dirk van der Hoeven
MetaGrad: Adaptation using Multiple Learning Rates in Online Learning. CoRR (2021)
Dirk van der Hoeven, Hédi Hadiji, Tim van Erven
Distributed Online Learning for Joint Regret with Communication Constraints. CoRR (2021)
Tim van Erven, Wouter M. Koolen, Dirk van der Hoeven
MetaGrad: Adaptation using Multiple Learning Rates in Online Learning. J. Mach. Learn. Res. 22 (2021)
Dirk van der Hoeven, Federico Fusco, Nicolò Cesa-Bianchi
Beyond Bandit Feedback in Online Multiclass Classification. CoRR (2021)
Dirk van der Hoeven, Federico Fusco, Nicolò Cesa-Bianchi
Beyond Bandit Feedback in Online Multiclass Classification. NeurIPS (2021)
Dirk van der Hoeven
Exploiting the Surrogate Gap in Online Multiclass Classification. NeurIPS (2020)
Tim van Erven, Dirk van der Hoeven, Wojciech Kotlowski, Wouter M. Koolen
Open Problem: Fast and Optimal Online Portfolio Selection. COLT (2020)
Dirk van der Hoeven, Ashok Cutkosky, Haipeng Luo
Comparator-Adaptive Convex Bandits. NeurIPS (2020)
Dirk van der Hoeven
Exploiting the Surrogate Gap in Online Multiclass Classification. CoRR (2020)
Dirk van der Hoeven, Ashok Cutkosky, Haipeng Luo
Comparator-adaptive Convex Bandits. CoRR (2020)
Dirk van der Hoeven
User-Specified Local Differential Privacy in Unconstrained Adaptive Online Learning. NeurIPS (2019)
Dirk van der Hoeven, Tim van Erven, Wojciech Kotlowski
The Many Faces of Exponential Weights in Online Learning. COLT (2018)
Dirk van der Hoeven, Tim van Erven, Wojciech Kotlowski
The Many Faces of Exponential Weights in Online Learning. CoRR (2018)