| Follow the leader if you can, hedge if you must S De Rooij, T Van Erven, PD Grünwald, WM Koolen The Journal of Machine Learning Research 15 (1), 1281-1316, 2014 | 210 | 2014 |
| Safe testing P Grünwald, R de Heide, WM Koolen 2020 Information Theory and Applications Workshop (ITA), 1-54, 2020 | 175 | 2020 |
| Hedging Structured Concepts. WM Koolen, MK Warmuth, J Kivinen COLT, 93-105, 2010 | 125 | 2010 |
| Mixture martingales revisited with applications to sequential tests and confidence intervals E Kaufmann, WM Koolen Journal of Machine Learning Research 22 (246), 1-44, 2021 | 112 | 2021 |
| Second-order quantile methods for experts and combinatorial games WM Koolen, T Van Erven Conference on Learning Theory, 1155-1175, 2015 | 112 | 2015 |
| Metagrad: Multiple learning rates in online learning T Van Erven, WM Koolen Advances in Neural Information Processing Systems 29, 2016 | 98 | 2016 |
| Admissible anytime-valid sequential inference must rely on nonnegative martingales A Ramdas, J Ruf, M Larsson, W Koolen arXiv preprint arXiv:2009.03167, 2020 | 88 | 2020 |
| Non-asymptotic pure exploration by solving games R Degenne, WM Koolen, P Ménard Advances in Neural Information Processing Systems 32, 2019 | 87 | 2019 |
| Pure exploration with multiple correct answers R Degenne, WM Koolen Advances in Neural Information Processing Systems 32, 2019 | 70 | 2019 |
| A closer look at adaptive regret D Adamskiy, WM Koolen, A Chernov, V Vovk Algorithmic Learning Theory: 23rd International Conference, ALT 2012, Lyon …, 2012 | 69 | 2012 |
| Universal codes from switching strategies WM Koolen, S de Rooij IEEE Transactions on Information Theory 59 (11), 7168-7185, 2013 | 66* | 2013 |
| Adaptive hedge T Erven, WM Koolen, S Rooij, P Grünwald Advances in Neural Information Processing Systems 24, 2011 | 57 | 2011 |
| Testing exchangeability: Fork-convexity, supermartingales and e-processes A Ramdas, J Ruf, M Larsson, WM Koolen International Journal of Approximate Reasoning 141, 83-109, 2022 | 54 | 2022 |
| Lipschitz and comparator-norm adaptivity in online learning Z Mhammedi, WM Koolen Conference on Learning Theory, 2858-2887, 2020 | 53 | 2020 |
| Monte-Carlo tree search by best arm identification E Kaufmann, WM Koolen Advances in Neural Information Processing Systems 30, 2017 | 51 | 2017 |
| A closer look at adaptive regret D Adamskiy, WM Koolen, A Chernov, V Vovk Journal of Machine Learning Research 17 (23), 1-21, 2016 | 49 | 2016 |
| Combining adversarial guarantees and stochastic fast rates in online learning WM Koolen, P Grünwald, T Van Erven Advances in Neural Information Processing Systems 29, 2016 | 45 | 2016 |
| Maximin action identification: A new bandit framework for games A Garivier, E Kaufmann, WM Koolen Conference on Learning Theory, 1028-1050, 2016 | 35 | 2016 |
| Structure adaptive algorithms for stochastic bandits R Degenne, H Shao, W Koolen International Conference on Machine Learning, 2443-2452, 2020 | 34 | 2020 |
| Sequential test for the lowest mean: From Thompson to Murphy sampling E Kaufmann, WM Koolen, A Garivier Advances in Neural Information Processing Systems 31, 2018 | 34 | 2018 |
Tim van ErvenAssociate professor at the University of Amsterdam, the Netherlands在 uva.nl 的电子邮件经过验证
