| The many faces of exponential weights in online learning D van der Hoeven, T van Erven, W Kotłowski arXiv preprint arXiv:1802.07543, 2018 | 42* | 2018 |
| User-specified local differential privacy in unconstrained adaptive online learning D van der Hoeven Advances in Neural Information Processing Systems 32, 14103-14112, 2019 | 33 | 2019 |
| Metagrad: Adaptation using multiple learning rates in online learning T Van Erven, WM Koolen, D Van der Hoeven Journal of Machine Learning Research 22 (161), 1-61, 2021 | 22 | 2021 |
| Open Problem: Fast and Optimal Online Portfolio Selection T Van Erven, D Van der Hoeven, W Kotłowski, WM Koolen Conference on Learning Theory, 3864-3869, 2020 | 21 | 2020 |
| A near-optimal best-of-both-worlds algorithm for online learning with feedback graphs C Rouyer, D van der Hoeven, N Cesa-Bianchi, Y Seldin Advances in Neural Information Processing Systems 35, 35035-35048, 2022 | 16 | 2022 |
| Nonstochastic Bandits and Experts with Arm-Dependent Delays D van der Hoeven, N Cesa-Bianchi arXiv preprint arXiv:2111.01589, 2021 | 13 | 2021 |
| Learning on the edge: Online learning with stochastic feedback graphs E Esposito, F Fusco, D van der Hoeven, N Cesa-Bianchi Advances in Neural Information Processing Systems 35, 34776-34788, 2022 | 12 | 2022 |
| Beyond Bandit Feedback in Online Multiclass Classification D van der Hoeven, F Fusco, N Cesa-Bianchi Advances in Neural Information Processing Systems 34, 13280-13291, 2021 | 11 | 2021 |
| Exploiting the Surrogate Gap in Online Multiclass Classification D van der Hoeven Advances in Neural Information Processing Systems 33, 2020 | 11 | 2020 |
| Comparator-Adaptive Convex Bandits D van der Hoeven, A Cutkosky, H Luo Advances in Neural Information Processing Systems 33, 2020 | 7 | 2020 |
| A regret-variance trade-off in online learning D Van der Hoeven, N Zhivotovskiy, N Cesa-Bianchi Advances in Neural Information Processing Systems 35, 35188-35200, 2022 | 5 | 2022 |
| Distributed online learning for joint regret with communication constraints D Van der Hoeven, H Hadiji, T van Erven International Conference on Algorithmic Learning Theory, 1003-1042, 2022 | 4 | 2022 |
| Online Newton Method for Bandit Convex Optimisation H Fokkema, D van der Hoeven, T Lattimore, JJ Mayo arXiv preprint arXiv:2406.06506, 2024 | 3 | 2024 |
| Nonstochastic Contextual Combinatorial Bandits L Zierahn, D van der Hoeven, N Cesa-Bianchi, G Neu International Conference on Artificial Intelligence and Statistics, 8771-8813, 2023 | 3 | 2023 |
| Is mirror descent a special case of exponential weights D van der Hoeven, T van Erven MSC Thesis. Available from: http://pub. math. leidenuniv. nl/~ hoevendvander, 2016 | 2 | 2016 |
| High-Probability Risk Bounds via Sequential Predictors D van der Hoeven, N Zhivotovskiy, N Cesa-Bianchi arXiv preprint arXiv:2308.07588, 2023 | 1 | 2023 |
| A Unified Analysis of Nonstochastic Delayed Feedback for Combinatorial Semi-Bandits, Linear Bandits, and MDPs D van der Hoeven, L Zierahn, T Lancewicki, A Rosenberg, ... The Thirty Sixth Annual Conference on Learning Theory, 1285-1321, 2023 | 1 | 2023 |
| Trading-off payments and accuracy in online classification with paid stochastic experts D Van Der Hoeven, C Pike-Burke, H Qiu, N Cesa-Bianchi International Conference on Machine Learning, 34809-34830, 2023 | | 2023 |
| Delayed Bandits: When Do Intermediate Observations Help? E Esposito, S Masoudian, H Qiu, D van der Hoeven, N Cesa-Bianchi, ... arXiv preprint arXiv:2305.19036, 2023 | | 2023 |
| The many faces of online learning D Hoeven Leiden University, 2021 | | 2021 |
