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ORCIDWouter M. Koolen
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2020 – today
- 2024
[c41]Élise Crepon, Aurélien Garivier, Wouter M. Koolen:
Sequential learning of the Pareto front for multi-objective bandits. AISTATS 2024: 3583-3591- 2023
- [c40]Hédi Hadiji, Sarah Sachs, Tim van Erven, Wouter M. Koolen:
Towards Characterizing the First-order Query Complexity of Learning (Approximate) Nash Equilibria in Zero-sum Matrix Games. NeurIPS 2023 - [i32]Hédi Hadiji, Sarah Sachs, Tim van Erven, Wouter M. Koolen:
Towards Characterizing the First-order Query Complexity of Learning (Approximate) Nash Equilibria in Zero-sum Matrix Games. CoRR abs/2304.12768 (2023) - [i31]Johannes Schmidt-Hieber, Wouter M. Koolen:
Hebbian learning inspired estimation of the linear regression parameters from queries. CoRR abs/2311.03483 (2023) - 2022
- [j13]Wouter M. Koolen
, Peter Grünwald:
Log-optimal anytime-valid E-values. Int. J. Approx. Reason. 141: 69-82 (2022) - [j12]Aaditya Ramdas, Johannes Ruf, Martin Larsson, Wouter M. Koolen:
Testing exchangeability: Fork-convexity, supermartingales and e-processes. Int. J. Approx. Reason. 141: 83-109 (2022) - [c39]Wouter M. Koolen, Muriel Felipe Pérez-Ortiz:
Luckiness in Multiscale Online Learning. NeurIPS 2022 - [i30]Johannes Ruf, Martin Larsson, Wouter M. Koolen, Aaditya Ramdas:
A composite generalization of Ville's martingale theorem. CoRR abs/2203.04485 (2022) - 2021
- [j11]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) - [j10]Emilie Kaufmann, Wouter M. Koolen:
Mixture Martingales Revisited with Applications to Sequential Tests and Confidence Intervals. J. Mach. Learn. Res. 22: 246:1-246:44 (2021) - [c38]Shubhada Agrawal, Sandeep Juneja, Wouter M. Koolen:
Regret Minimization in Heavy-Tailed Bandits. COLT 2021: 26-62 - [c37]Tim van Erven, Sarah Sachs, Wouter M. Koolen, Wojciech Kotlowski:
Robust Online Convex Optimization in the Presence of Outliers. COLT 2021: 4174-4194 - [c36]Yoan Russac, Christina Katsimerou, Dennis Bohle, Olivier Cappé, Aurélien Garivier, Wouter M. Koolen:
A/B/n Testing with Control in the Presence of Subpopulations. NeurIPS 2021: 25100-25110 - [c35]Shubhada Agrawal, Wouter M. Koolen, Sandeep Juneja:
Optimal Best-Arm Identification Methods for Tail-Risk Measures. NeurIPS 2021: 25578-25590 - [i29]Aaditya Ramdas, Johannes Ruf, Martin Larsson, Wouter M. Koolen:
How can one test if a binary sequence is exchangeable? Fork-convex hulls, supermartingales, and Snell envelopes. CoRR abs/2102.00630 (2021) - [i28]Shubhada Agrawal, Sandeep Juneja, Wouter M. Koolen:
Regret Minimization in Heavy-Tailed Bandits. CoRR abs/2102.03734 (2021) - [i27]Tim van Erven, Wouter M. Koolen, Dirk van der Hoeven:
MetaGrad: Adaptation using Multiple Learning Rates in Online Learning. CoRR abs/2102.06622 (2021) - [i26]Tim van Erven, Sarah Sachs, Wouter M. Koolen, Wojciech Kotlowski:
Robust Online Convex Optimization in the Presence of Outliers. CoRR abs/2107.01881 (2021) - [i25]Yoan Russac, Christina Katsimerou, Dennis Bohle, Olivier Cappé, Aurélien Garivier, Wouter M. Koolen:
A/B/n Testing with Control in the Presence of Subpopulations. CoRR abs/2110.15573 (2021) - 2020
- [c34]Zakaria Mhammedi, Wouter M. Koolen:
Lipschitz and Comparator-Norm Adaptivity in Online Learning. COLT 2020: 2858-2887 - [c33]Tim van Erven, Dirk van der Hoeven, Wojciech Kotlowski, Wouter M. Koolen:
Open Problem: Fast and Optimal Online Portfolio Selection. COLT 2020: 3864-3869 - [c32]Rémy Degenne, Han Shao, Wouter M. Koolen:
Structure Adaptive Algorithms for Stochastic Bandits. ICML 2020: 2443-2452 - [c31]Peter Grünwald, Rianne de Heide, Wouter M. Koolen:
Safe Testing. ITA 2020: 1-54 - [i24]Zakaria Mhammedi, Wouter M. Koolen:
Lipschitz and Comparator-Norm Adaptivity in Online Learning. CoRR abs/2002.12242 (2020) - [i23]Rémy Degenne, Han Shao, Wouter M. Koolen:
Structure Adaptive Algorithms for Stochastic Bandits. CoRR abs/2007.00969 (2020) - [i22]Shubhada Agrawal, Wouter M. Koolen, Sandeep Juneja:
Optimal Best-Arm Identification Methods for Tail-Risk Measures. CoRR abs/2008.07606 (2020)
2010 – 2019
- 2019
- [c30]Zakaria Mhammedi, Wouter M. Koolen, Tim van Erven:
Lipschitz Adaptivity with Multiple Learning Rates in Online Learning. COLT 2019: 2490-2511 - [c29]Thijs van Ommen, Wouter M. Koolen, Peter D. Grünwald:
Efficient Algorithms for Minimax Decisions Under Tree-Structured Incompleteness. ECSQARU 2019: 336-347 - [c28]Rémy Degenne, Wouter M. Koolen, Pierre Ménard:
Non-Asymptotic Pure Exploration by Solving Games. NeurIPS 2019: 14465-14474 - [c27]Rémy Degenne, Wouter M. Koolen:
Pure Exploration with Multiple Correct Answers. NeurIPS 2019: 14564-14573 - [i21]Rémy Degenne, Wouter M. Koolen:
Pure Exploration with Multiple Correct Answers. CoRR abs/1902.03475 (2019) - [i20]Zakaria Mhammedi, Wouter M. Koolen, Tim van Erven:
Lipschitz Adaptivity with Multiple Learning Rates in Online Learning. CoRR abs/1902.10797 (2019) - [i19]Peter Grünwald, Rianne de Heide, Wouter M. Koolen:
Safe Testing. CoRR abs/1906.07801 (2019) - [i18]Rémy Degenne, Wouter M. Koolen, Pierre Ménard:
Non-Asymptotic Pure Exploration by Solving Games. CoRR abs/1906.10431 (2019) - 2018
- [c26]Emilie Kaufmann, Wouter M. Koolen, Aurélien Garivier:
Sequential Test for the Lowest Mean: From Thompson to Murphy Sampling. NeurIPS 2018: 6335-6345 - [i17]Emilie Kaufmann, Wouter M. Koolen, Aurélien Garivier:
Sequential Test for the Lowest Mean: From Thompson to Murphy Sampling. CoRR abs/1806.00973 (2018) - [i16]Emilie Kaufmann, Wouter M. Koolen:
Mixture Martingales Revisited with Applications to Sequential Tests and Confidence Intervals. CoRR abs/1811.11419 (2018) - 2017
- [c25]Wojciech Kotlowski, Wouter M. Koolen, Alan Malek:
Random Permutation Online Isotonic Regression. NIPS 2017: 4180-4189 - [c24]Emilie Kaufmann, Wouter M. Koolen:
Monte-Carlo Tree Search by Best Arm Identification. NIPS 2017: 4897-4906 - [i15]Emilie Kaufmann, Wouter M. Koolen:
Monte-Carlo Tree Search by Best Arm Identification. CoRR abs/1706.02986 (2017) - 2016
- [j9]Thijs van Ommen, Wouter M. Koolen, Thijs E. Feenstra, Peter D. Grünwald:
Robust probability updating. Int. J. Approx. Reason. 74: 30-57 (2016) - [j8]Dmitry Adamskiy, Wouter M. Koolen, Alexey V. Chernov, Vladimir Vovk:
A Closer Look at Adaptive Regret. J. Mach. Learn. Res. 17: 23:1-23:21 (2016) - [c23]Aurélien Garivier, Emilie Kaufmann, Wouter M. Koolen:
Maximin Action Identification: A New Bandit Framework for Games. COLT 2016: 1028-1050 - [c22]Tim van Erven, Wouter M. Koolen:
MetaGrad: Multiple Learning Rates in Online Learning. NIPS 2016: 3666-3674 - [c21]Wouter M. Koolen, Peter Grünwald, Tim van Erven:
Combining Adversarial Guarantees and Stochastic Fast Rates in Online Learning. NIPS 2016: 4457-4465 - [i14]Aurélien Garivier, Emilie Kaufmann, Wouter M. Koolen:
Maximin Action Identification: A New Bandit Framework for Games. CoRR abs/1602.04676 (2016) - [i13]Wojciech Kotlowski, Wouter M. Koolen, Alan Malek:
Online Isotonic Regression. CoRR abs/1603.04190 (2016) - [i12]Tim van Erven, Wouter M. Koolen:
MetaGrad: Multiple Learning Rates in Online Learning. CoRR abs/1604.08740 (2016) - [i11]Wouter M. Koolen, Peter Grünwald, Tim van Erven:
Combining Adversarial Guarantees and Stochastic Fast Rates in Online Learning. CoRR abs/1605.06439 (2016) - [i10]Wouter M. Koolen:
Robust and Adaptive Methods for Sequential Decision Making. ERCIM News 2016(107) (2016) - 2015
- [c20]Peter L. Bartlett, Wouter M. Koolen, Alan Malek, Eiji Takimoto, Manfred K. Warmuth:
Minimax Fixed-Design Linear Regression. COLT 2015: 226-239 - [c19]Wouter M. Koolen, Tim van Erven:
Second-order Quantile Methods for Experts and Combinatorial Games. COLT 2015: 1155-1175 - [c18]Wouter M. Koolen, Manfred K. Warmuth, Dmitry Adamskiy:
Open Problem: Online Sabotaged Shortest Path. COLT 2015: 1764-1766 - [c17]Wouter M. Koolen, Alan Malek, Peter L. Bartlett, Yasin Abbasi-Yadkori:
Minimax Time Series Prediction. NIPS 2015: 2557-2565 - [i9]Wouter M. Koolen, Tim van Erven:
Second-order Quantile Methods for Experts and Combinatorial Games. CoRR abs/1502.08009 (2015) - [i8]Thijs van Ommen, Wouter M. Koolen, Thijs E. Feenstra, Peter D. Grünwald:
Worst-case Optimal Probability Updating. CoRR abs/1512.03223 (2015) - 2014
- [j7]Steven de Rooij, Tim van Erven, Peter D. Grünwald, Wouter M. Koolen:
Follow the leader if you can, hedge if you must. J. Mach. Learn. Res. 15(1): 1281-1316 (2014) - [j6]Manfred K. Warmuth, Wouter M. Koolen, David P. Helmbold:
Combining initial segments of lists. Theor. Comput. Sci. 519: 29-45 (2014) - [j5]Wouter M. Koolen, Vladimir Vovk:
Buy low, sell high. Theor. Comput. Sci. 558: 144-158 (2014) - [c16]Manfred K. Warmuth, Wouter M. Koolen:
Open Problem: Shifting Experts on Easy Data. COLT 2014: 1295-1298 - [c15]Wouter M. Koolen, Tim van Erven, Peter Grünwald:
Learning the Learning Rate for Prediction with Expert Advice. NIPS 2014: 2294-2302 - [c14]Wouter M. Koolen, Alan Malek, Peter L. Bartlett:
Efficient Minimax Strategies for Square Loss Games. NIPS 2014: 3230-3238 - 2013
- [j4]Wouter M. Koolen, Steven de Rooij:
Switching investments. Theor. Comput. Sci. 473: 61-76 (2013) - [j3]Wouter M. Koolen, Steven de Rooij:
Universal Codes From Switching Strategies. IEEE Trans. Inf. Theory 59(11): 7168-7185 (2013) - [c13]Wouter M. Koolen, Jiazhong Nie, Manfred K. Warmuth:
Learning a set of directions. COLT 2013: 851-866 - [c12]Tim Scarfe, Wouter M. Koolen, Yuri Kalnishkan:
A Long-Range Self-similarity Approach to Segmenting DJ Mixed Music Streams. AIAI 2013: 235-244 - [c11]Wouter M. Koolen:
The Pareto Regret Frontier. NIPS 2013: 863-871 - [i7]Steven de Rooij, Tim van Erven, Peter D. Grünwald, Wouter M. Koolen:
Follow the Leader If You Can, Hedge If You Must. CoRR abs/1301.0534 (2013) - [i6]Wouter M. Koolen, Steven de Rooij:
Universal Codes from Switching Strategies. CoRR abs/1311.6536 (2013) - 2012
- [c10]Dmitry Adamskiy, Wouter M. Koolen, Alexey V. Chernov, Vladimir Vovk:
A Closer Look at Adaptive Regret. ALT 2012: 290-304 - [c9]Wouter M. Koolen, Vladimir Vovk:
Buy Low, Sell High. ALT 2012: 335-349 - [c8]Wouter M. Koolen, Dmitry Adamskiy, Manfred K. Warmuth:
Putting Bayes to sleep. NIPS 2012: 135-143 - 2011
- [j2]Harry Buhrman, Peter T. S. van der Gulik, Steven Kelk, Wouter M. Koolen, Leen Stougie:
Some Mathematical Refinements Concerning Error Minimization in the Genetic Code. IEEE ACM Trans. Comput. Biol. Bioinform. 8(5): 1358-1372 (2011) - [c7]Manfred K. Warmuth, Wouter M. Koolen, David P. Helmbold:
Combining Initial Segments of Lists. ALT 2011: 219-233 - [c6]Wouter M. Koolen, Wojciech Kotlowski, Manfred K. Warmuth:
Learning Eigenvectors for Free. NIPS 2011: 945-953 - [c5]Tim van Erven, Peter Grunwald, Wouter M. Koolen, Steven de Rooij:
Adaptive Hedge. NIPS 2011: 1656-1664 - 2010
- [c4]Wouter M. Koolen, Steven de Rooij:
Switching Investments. ALT 2010: 239-254 - [c3]Wouter M. Koolen, Manfred K. Warmuth, Jyrki Kivinen:
Hedging Structured Concepts. COLT 2010: 93-105 - [i5]Wouter M. Koolen, Tim van Erven:
Switching between Hidden Markov Models using Fixed Share. CoRR abs/1008.4532 (2010) - [i4]Wouter M. Koolen, Tim van Erven:
Freezing and Sleeping: Tracking Experts that Learn by Evolving Past Posteriors. CoRR abs/1008.4654 (2010)
2000 – 2009
- 2009
- [j1]Edgar G. Daylight, Wouter M. Koolen, Paul M. B. Vitányi:
Time-bounded incompressibility of compressible strings and sequences. Inf. Process. Lett. 109(18): 1055-1059 (2009) - 2008
- [c2]Wouter M. Koolen, Steven de Rooij:
Combining Expert Advice Efficiently. COLT 2008: 275-286 - [c1]Martin Ziegler, Wouter M. Koolen:
Kolmogorov Complexity Theory over the Reals. CCA 2008: 153-169 - [i3]Wouter M. Koolen, Steven de Rooij:
Combining Expert Advice Efficiently. CoRR abs/0802.2015 (2008) - [i2]Martin Ziegler, Wouter M. Koolen:
Kolmogorov Complexity Theory over the Reals. CoRR abs/0802.2027 (2008) - [i1]Edgar G. Daylight, Wouter M. Koolen, Paul M. B. Vitányi:
On Time-Bounded Incompressibility of Compressible Strings. CoRR abs/0809.2965 (2008)
Coauthor Index
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last updated on 2024-09-13 00:41 CEST by the dblp team
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