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Dirk van der Hoeven
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2020 – today
- 2024
- [c16]Hidde Fokkema, Dirk van der Hoeven, Tor Lattimore, Jack J. Mayo:
Online Newton Method for Bandit Convex Optimisation Extended Abstract. COLT 2024: 1713-1714 - [i15]Hidde Fokkema, Dirk van der Hoeven, Tor Lattimore, Jack J. Mayo:
Online Newton Method for Bandit Convex Optimisation. CoRR abs/2406.06506 (2024) - 2023
- [c15]Lukas Zierahn, Dirk van der Hoeven, Nicolò Cesa-Bianchi, Gergely Neu:
Nonstochastic Contextual Combinatorial Bandits. AISTATS 2023: 8771-8813 - [c14]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: 1285-1321 - [c13]Emmanuel Esposito, Saeed Masoudian, Hao Qiu, Dirk van der Hoeven, Nicolò Cesa-Bianchi, Yevgeny Seldin:
Delayed Bandits: When Do Intermediate Observations Help? ICML 2023: 9374-9395 - [c12]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: 34809-34830 - [i14]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 abs/2305.08629 (2023) - [i13]Emmanuel Esposito, Saeed Masoudian, Hao Qiu, Dirk van der Hoeven, Nicolò Cesa-Bianchi, Yevgeny Seldin:
Delayed Bandits: When Do Intermediate Observations Help? CoRR abs/2305.19036 (2023) - [i12]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 abs/2307.00836 (2023) - [i11]Dirk van der Hoeven, Nikita Zhivotovskiy, Nicolò Cesa-Bianchi:
High-Probability Risk Bounds via Sequential Predictors. CoRR abs/2308.07588 (2023) - 2022
- [c11]Dirk van der Hoeven, Nicolò Cesa-Bianchi:
Nonstochastic Bandits and Experts with Arm-Dependent Delays. AISTATS 2022: 2022-2044 - [c10]Dirk van der Hoeven, Hédi Hadiji, Tim van Erven:
Distributed Online Learning for Joint Regret with Communication Constraints. ALT 2022: 1003-1042 - [c9]Emmanuel Esposito, Federico Fusco, Dirk van der Hoeven, Nicolò Cesa-Bianchi:
Learning on the Edge: Online Learning with Stochastic Feedback Graphs. NeurIPS 2022 - [c8]Dirk van der Hoeven, Nikita Zhivotovskiy, Nicolò Cesa-Bianchi:
A Regret-Variance Trade-Off in Online Learning. NeurIPS 2022 - [c7]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 - [i10]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 abs/2206.00557 (2022) - [i9]Dirk van der Hoeven, Nikita Zhivotovskiy, Nicolò Cesa-Bianchi:
A Regret-Variance Trade-Off in Online Learning. CoRR abs/2206.02656 (2022) - [i8]Emmanuel Esposito, Federico Fusco, Dirk van der Hoeven, Nicolò Cesa-Bianchi:
Learning on the Edge: Online Learning with Stochastic Feedback Graphs. CoRR abs/2210.04229 (2022) - 2021
- [j1]Tim van Erven, Wouter M. Koolen, Dirk van der Hoeven:
MetaGrad: Adaptation using Multiple Learning Rates in Online Learning. J. Mach. Learn. Res. 22: 161:1-161:61 (2021) - [c6]Dirk van der Hoeven, Federico Fusco, Nicolò Cesa-Bianchi:
Beyond Bandit Feedback in Online Multiclass Classification. NeurIPS 2021: 13280-13291 - [i7]Tim van Erven, Wouter M. Koolen, Dirk van der Hoeven:
MetaGrad: Adaptation using Multiple Learning Rates in Online Learning. CoRR abs/2102.06622 (2021) - [i6]Dirk van der Hoeven, Hédi Hadiji, Tim van Erven:
Distributed Online Learning for Joint Regret with Communication Constraints. CoRR abs/2102.07521 (2021) - [i5]Dirk van der Hoeven, Federico Fusco, Nicolò Cesa-Bianchi:
Beyond Bandit Feedback in Online Multiclass Classification. CoRR abs/2106.03596 (2021) - [i4]Dirk van der Hoeven, Nicolò Cesa-Bianchi:
Nonstochastic Bandits and Experts with Arm-Dependent Delays. CoRR abs/2111.01589 (2021) - 2020
- [c5]Tim van Erven, Dirk van der Hoeven, Wojciech Kotlowski, Wouter M. Koolen:
Open Problem: Fast and Optimal Online Portfolio Selection. COLT 2020: 3864-3869 - [c4]Dirk van der Hoeven:
Exploiting the Surrogate Gap in Online Multiclass Classification. NeurIPS 2020 - [c3]Dirk van der Hoeven, Ashok Cutkosky, Haipeng Luo:
Comparator-Adaptive Convex Bandits. NeurIPS 2020 - [i3]Dirk van der Hoeven, Ashok Cutkosky, Haipeng Luo:
Comparator-adaptive Convex Bandits. CoRR abs/2007.08448 (2020) - [i2]Dirk van der Hoeven:
Exploiting the Surrogate Gap in Online Multiclass Classification. CoRR abs/2007.12618 (2020)
2010 – 2019
- 2019
- [c2]Dirk van der Hoeven:
User-Specified Local Differential Privacy in Unconstrained Adaptive Online Learning. NeurIPS 2019: 14080-14089 - 2018
- [c1]Dirk van der Hoeven, Tim van Erven, Wojciech Kotlowski:
The Many Faces of Exponential Weights in Online Learning. COLT 2018: 2067-2092 - [i1]Dirk van der Hoeven, Tim van Erven, Wojciech Kotlowski:
The Many Faces of Exponential Weights in Online Learning. CoRR abs/1802.07543 (2018)
Coauthor Index
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last updated on 2024-09-13 01:40 CEST by the dblp team
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