2024
2023
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Towards characterizing the first-order query complexity of learning (approximate) Nash equilibria in zero-sum matrix games
Hédi Hadiji, Sarah Sachs, Tim van Erven, Wouter M. Koolen
In Advances in Neural Information Processing Systems (NeurIPS) 35, December 2023.
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Hebbian learning inspired estimation of the linear regression parameters from queries
Johannes Schmidt-Hieber, Wouter M. Koolen
ArXiv, November 2023.
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A composite generalization of Ville's martingale theorem
Johannes Ruf, Martin Larsson, Wouter M. Koolen, Aaditya Ramdas
Electronic Journal of Probability, 28:1–21, October 2023.
2022
2021
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A/B/n testing with control in the presence of subpopulations
Yoan Russac, Christina Katsimerou, Dennis Bohle, Olivier Cappé, Aurélien Garivier, Wouter M. Koolen
In Advances in Neural Information Processing Systems (NeurIPS) 34, December 2021.
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Optimal best-arm identification methods for tail-risk measures
Shubhada Agrawal, Wouter M. Koolen, Sandeep Juneja
In Advances in Neural Information Processing Systems (NeurIPS) 34, December 2021.
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Mixture martingales revisited with applications to sequential tests and confidence intervals
Emilie Kaufmann, Wouter M. Koolen
Journal of Machine Learning Research, 22(246):1–44, November 2021.
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Log-optimal anytime-valid E-values
Wouter M. Koolen, Peter Grünwald
International Journal of Approximate Reasoning, September 2021.
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Robust online convex optimization in the presence of outliers
Sarah Sachs, Tim van Erven, Wouter M. Koolen, Wojciech Kotłowski
In Proceedings of the 34th Annual Conference on Learning Theory (COLT), pages 4174–4194, August 2021.
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Regret minimization in heavy-tailed bandits
Shubhada Agrawal, Sandeep Juneja, Wouter M. Koolen
In Proceedings of the 34th Annual Conference on Learning Theory (COLT), pages 26–62, August 2021.
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Metagrad: Adaptation using multiple learning rates in online learning
Tim van Erven, Wouter M. Koolen, Dirk van der Hoeven
Journal of Machine Learning Research, 22(161):1–61, July 2021.
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Testing exchangeability: fork-convexity, supermartingales and e-processes
Aaditya Ramdas, Johannes Ruf, Martin Larsson, Wouter M. Koolen
International Journal of Approximate Reasoning, July 2021.
2020
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Admissible anytime-valid sequential inference must rely on nonnegative martingales
Aaditya Ramdas, Johannes Ruf, Martin Larsson, Wouter M. Koolen
ArXiv, September 2020.
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Structure adaptive algorithms for stochastic bandits
Rémy Degenne, Han Shao, Wouter M. Koolen
In Proceedings of the 37th International Conference on Machine Learning (ICML), July 2020.
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Lipschitz and comparator-norm adaptivity in online learning
Zakaria Mhammedi, Wouter M. Koolen
In Proceedings of the 33rd Annual Conference on Learning Theory (COLT), pages 2858–2887, July 2020.
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Open problem: Fast and optimal online portfolio selection
Tim van Erven, Dirk van der Hoeven, Wojciech Kotłowski, Wouter M. Koolen
In Proceedings of the 33rd Annual Conference on Learning Theory (COLT), July 2020.
2019
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Non-asymptotic pure exploration by solving games
Rémy Degenne, Wouter M. Koolen, Pierre Ménard
In Advances in Neural Information Processing Systems (NeurIPS) 32, pages 14492–14501. Curran Associates, Inc., December 2019.
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Pure exploration with multiple correct answers
Rémy Degenne, Wouter M. Koolen
In Advances in Neural Information Processing Systems (NeurIPS) 32, pages 14591–14600. Curran Associates, Inc., December 2019.
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Efficient algorithms for minimax decisions under tree-structured incompleteness
Thijs van Ommen, Wouter M. Koolen, Peter Grünwald
In Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU), pages 336–347. Springer International Publishing, September 2019.
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Safe testing
Peter Grünwald, Rianne de Heide, Wouter M. Koolen
ArXiv, June 2019.
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Lipschitz adaptivity with multiple learning rates in online learning
Zakaria Mhammedi, Wouter M. Koolen, Tim van Erven
In Proceedings of the 32nd Annual Conference on Learning Theory (COLT), pages 2490–2511, June 2019.
2018
2017
2016
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Combining adversarial guarantees and stochastic fast rates in online learning
Wouter M. Koolen, Peter Grünwald, Tim van Erven
In Advances in Neural Information Processing Systems (NeurIPS) 29, pages 4457–4465, December 2016.
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MetaGrad: Multiple learning rates in online learning
Tim van Erven, Wouter M. Koolen
In Advances in Neural Information Processing Systems (NeurIPS) 29, pages 3666–3674, December 2016.
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Maximin action identification: A new bandit framework for games
Aurélien Garivier, Emilie Kaufmann, Wouter M. Koolen
In Proceedings of the 29th Annual Conference on Learning Theory (COLT), pages 1028 – 1050, June 2016.
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Online isotonic regression
Wojciech Kotłowski, Wouter M. Koolen, Alan Malek
In Proceedings of the 29th Annual Conference on Learning Theory (COLT), pages 1165–1189, June 2016.
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A closer look at adaptive regret
Dmitry Adamskiy, Wouter M. Koolen, Alexey Chernov, Vladimir Vovk
Journal of Machine Learning Research, 17(23):1–21, April 2016.
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Robust probability updating
Thijs van Ommen, Wouter M. Koolen, Thijs E. Feenstra, Peter Grünwald
International Journal of Approximate Reasoning, 74:30–57, April 2016.
2015
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Minimax time series prediction
Wouter M. Koolen, Alan Malek, Peter L. Bartlett, Yasin Abbasi-Yadkori
In Advances in Neural Information Processing Systems (NeurIPS) 28, pages 2548–2556, December 2015.
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Open problem: Online sabotaged shortest path
Wouter M. Koolen, Manfred K. Warmuth, Dmitry Adamskiy
In Proceedings of the 28th Annual Conference on Learning Theory (COLT), pages 1764–1766, June 2015.
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Minimax fixed-design linear regression
Peter L. Bartlett, Wouter M. Koolen, Alan Malek, Manfred K. Warmuth, Eiji Takimoto
In Proceedings of the 28th Annual Conference on Learning Theory (COLT), pages 226–239, June 2015.
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Second-order quantile methods for experts and combinatorial games
Wouter M. Koolen, Tim van Erven
In Proceedings of the 28th Annual Conference on Learning Theory (COLT), pages 1155–1175, June 2015.
2014
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Efficient minimax strategies for square loss games
Wouter M. Koolen, Alan Malek, Peter L. Bartlett
In Advances in Neural Information Processing Systems (NeurIPS) 27, pages 3230–3238, December 2014.
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Learning the learning rate for prediction with expert advice
Wouter M. Koolen, Tim van Erven, Peter Grünwald
In Advances in Neural Information Processing Systems (NeurIPS) 27, pages 2294–2302, December 2014.
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Buy low, sell high
Wouter M. Koolen, Vladimir Vovk
Theoretical Computer Science, 558(0):144–158, October 2014. The special issue on Algorithmic Learning Theory for ALT 2012.
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Open problem: Shifting experts on easy data
Manfred K. Warmuth, Wouter M. Koolen
In Proceedings of the 27th Annual Conference on Learning Theory (COLT), pages 1295–1298, June 2014.
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Follow the leader if you can, Hedge if you must
Steven de Rooij, Tim van Erven, Peter Grünwald, Wouter M. Koolen
Journal of Machine Learning Research, 15:1281–1316, April 2014.
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Combining initial segments of lists
Manfred K. Warmuth, Wouter M. Koolen, David P. Helmbold
Theoretical Computer Science, 519:29–45, January 2014. The special issue on Algorithmic Learning Theory for ALT 2011.
2013
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The Pareto regret frontier
Wouter M. Koolen
In Advances in Neural Information Processing Systems (NeurIPS) 26, pages 863–871, December 2013.
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Universal codes from switching strategies
Wouter M. Koolen, Steven de Rooij
IEEE Transactions on Information Theory, 59(11):7168–7185, November 2013.
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A long-range self-similarity approach to segmenting DJ mixed music streams
Tim Scarfe, Wouter M. Koolen, Yuri Kalnishkan
In Artificial Intelligence Applications and Innovations, volume 412 of IFIP Advances in Information and Communication Technology, pages 235–244. Springer, September 2013.
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Learning a set of directions
Wouter M. Koolen, Jiazhong Nie, Manfred K. Warmuth
In Proceedings of the 26th Annual Conference on Learning Theory (COLT), June 2013.
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Switching investments
Wouter M. Koolen, Steven de Rooij
Theoretical Computer Science, 473(0):61–76, February 2013. The special issue on Algorithmic Learning Theory for ALT 2010.
2012
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Putting Bayes to sleep
Wouter M. Koolen, Dmitry Adamskiy, Manfred K. Warmuth
In Advances in Neural Information Processing Systems (NeurIPS) 25, pages 135–143, December 2012.
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A closer look at adaptive regret
Dmitry Adamskiy, Wouter M. Koolen, Alexey Chernov, Vladimir Vovk
In Proceedings of the 23rd International Conference on Algorithmic Learning Theory (ALT), LNAI 7568, pages 290–304. Springer, October 2012.
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Buy low, sell high
Wouter M. Koolen, Vladimir Vovk
In Proceedings of the 23rd International Conference on Algorithmic Learning Theory (ALT), LNAI 7568, pages 335–349. Springer, October 2012.
2011
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Learning eigenvectors for free
Wouter M. Koolen, Wojciech Kotłowski, Manfred K. Warmuth
In Advances in Neural Information Processing Systems (NeurIPS) 24, pages 945–953, December 2011.
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Adaptive Hedge
Tim van Erven, Steven de Rooij, Wouter M. Koolen, Peter Grünwald
In Advances in Neural Information Processing Systems (NeurIPS) 24, pages 1656–1664, December 2011.
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Combining initial segments of lists
Manfred K. Warmuth, Wouter M. Koolen, David P. Helmbold
In Proceedings of the 22nd International Conference on Algorithmic Learning Theory (ALT), LNAI 6925, pages 219–233. Springer, October 2011.
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Probability-free pricing of adjusted american lookbacks
A. Philip Dawid, Steven de Rooij, Peter Grünwald, Wouter M. Koolen, Glenn Shafer, Alexander Shen, Nikolai Vereshchagin, Vladimir Vovk
ArXiv, August 2011.
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Some mathematical refinements concerning error minimization in the genetic code
Harry Buhrman, Peter T. S. van der Gulik, Steven M. Kelk, Wouter M. Koolen, Leen Stougie
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), 8:1358–1372, March 2011.
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Combining Strategies Efficiently: High-quality Decisions from Conflicting Advice
Wouter M. Koolen
PhD thesis, Institute of Logic, Language and Computation (ILLC), University of Amsterdam, January 2011. cum laude.
2010
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Switching investments
Wouter M. Koolen, Steven de Rooij
In Proceedings of the 21st International Conference on Algorithmic Learning Theory (ALT), LNAI 6331, pages 239–254. Springer, October 2010.
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Hedging structured concepts
Wouter M. Koolen, Manfred K. Warmuth, Jyrki Kivinen
In Proceedings of the 23rd Annual Conference on Learning Theory (COLT), pages 93–105, June 2010.
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Switching between hidden Markov models using Fixed Share
Wouter M. Koolen, Tim van Erven
Computing Research Repository (CoRR), abs/1008.4532, February 2010.
2009
2008
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Kolmogorov complexity theory over the reals
Martin Ziegler, Wouter M. Koolen
Electronic Notes in Theoretical Computer Science (ENTCS), 221:153–169, December 2008.
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Combining expert advice efficiently
Wouter M. Koolen, Steven de Rooij
In Proceedings of the 21st Annual Conference on Learning Theory (COLT), pages 275–286, June 2008.
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Combining expert advice efficiently
Wouter M. Koolen, Steven de Rooij
Computing Research Repository (CoRR), abs/0802.2015, February 2008.
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Temporary unavailability logic and general modification logic
Wouter M. Koolen
ILLC Prepublication Series, January 2008.
2006