Combining Expert Advice Efficiently. - Wouter M. Koolen; Steven de Rooij (COLT, 2008)

On Time-Bounded Incompressibility of Compressible Strings - Edgar G. Daylight; Wouter M. Koolen; Paul M. B. Vitányi (CoRR, 2008)

Kolmogorov Complexity Theory over the Reals. - Martin Ziegler 001; Wouter M. Koolen (CCA, 2008)

Time-bounded incompressibility of compressible strings and sequences. - Edgar G. Daylight; Wouter M. Koolen; Paul M. B. Vitányi (Inf. Process. Lett., 2009)

Hedging Structured Concepts. - Wouter M. Koolen; Manfred K. Warmuth; Jyrki Kivinen (COLT, 2010)

Switching between Hidden Markov Models using Fixed Share - Wouter M. Koolen; Tim van Erven (CoRR, 2010)

Freezing and Sleeping: Tracking Experts that Learn by Evolving Past Posteriors - Wouter M. Koolen; Tim van Erven (CoRR, 2010)

Adaptive Hedge. - Tim van Erven; Peter Grunwald; Wouter M. Koolen; Steven de Rooij (NIPS, 2011)

Learning Eigenvectors for Free. - Wouter M. Koolen; Wojciech Kotlowski; Manfred K. Warmuth (NIPS, 2011)

Some Mathematical Refinements Concerning Error Minimization in the Genetic Code. - Harry Buhrman; Peter T. S. van der Gulik; Steven Kelk; Wouter M. Koolen; Leen Stougie (IEEE ACM Trans. Comput. Biol. Bioinform., 2011)

Putting Bayes to sleep. - Wouter M. Koolen; Dmitry Adamskiy; Manfred K. Warmuth (NIPS, 2012)

Learning a set of directions. - Wouter M. Koolen; Jiazhong Nie; Manfred K. Warmuth (COLT, 2013)

A Long-Range Self-similarity Approach to Segmenting DJ Mixed Music Streams. - Tim Scarfe; Wouter M. Koolen; Yuri Kalnishkan (AIAI, 2013)

The Pareto Regret Frontier. - Wouter M. Koolen (NIPS, 2013)

Switching investments. - Wouter M. Koolen; Steven de Rooij (Theor. Comput. Sci., 2013)

Universal Codes From Switching Strategies. - Wouter M. Koolen; Steven de Rooij (IEEE Trans. Inf. Theory, 2013)

Open Problem: Shifting Experts on Easy Data. - Manfred K. Warmuth; Wouter M. Koolen (COLT, 2014)

Learning the Learning Rate for Prediction with Expert Advice. - Wouter M. Koolen; Tim van Erven; Peter Grünwald (NIPS, 2014)

Efficient Minimax Strategies for Square Loss Games. - Wouter M. Koolen; Alan Malek; Peter L. Bartlett (NIPS, 2014)

Follow the leader if you can, hedge if you must. - Steven de Rooij; Tim van Erven; Peter D. Grünwald; Wouter M. Koolen (J. Mach. Learn. Res., 2014)

Buy low, sell high. - Wouter M. Koolen; Vladimir Vovk (Theor. Comput. Sci., 2014)

Combining initial segments of lists. - Manfred K. Warmuth; Wouter M. Koolen; David P. Helmbold (Theor. Comput. Sci., 2014)

Minimax Fixed-Design Linear Regression. - Peter L. Bartlett; Wouter M. Koolen; Alan Malek; Eiji Takimoto; Manfred K. Warmuth (COLT, 2015)

Second-order Quantile Methods for Experts and Combinatorial Games. - Wouter M. Koolen; Tim van Erven (COLT, 2015)

Open Problem: Online Sabotaged Shortest Path. - Wouter M. Koolen; Manfred K. Warmuth; Dmitry Adamskiy (COLT, 2015)

Minimax Time Series Prediction. - Wouter M. Koolen; Alan Malek; Peter L. Bartlett; Yasin Abbasi-Yadkori (NIPS, 2015)

Worst-case Optimal Probability Updating. - Thijs van Ommen; Wouter M. Koolen; Thijs E. Feenstra; Peter D. Grünwald (CoRR, 2015)

Maximin Action Identification: A New Bandit Framework for Games. - Aurélien Garivier; Emilie Kaufmann; Wouter M. Koolen (COLT, 2016)

MetaGrad: Multiple Learning Rates in Online Learning. - Tim van Erven; Wouter M. Koolen (NIPS, 2016)

Combining Adversarial Guarantees and Stochastic Fast Rates in Online Learning. - Wouter M. Koolen; Peter Grünwald; Tim van Erven (NIPS, 2016)

Online Isotonic Regression. - Wojciech Kotlowski; Wouter M. Koolen; Alan Malek (CoRR, 2016)

Robust and Adaptive Methods for Sequential Decision Making. - Wouter M. Koolen (ERCIM News, 2016)

Robust probability updating. - Thijs van Ommen; Wouter M. Koolen; Thijs E. Feenstra; Peter D. Grünwald (Int. J. Approx. Reason., 2016)

A Closer Look at Adaptive Regret. - Dmitry Adamskiy; Wouter M. Koolen; Alexey V. Chernov; Vladimir Vovk (J. Mach. Learn. Res., 2016)

Monte-Carlo Tree Search by Best Arm Identification. - Emilie Kaufmann; Wouter M. Koolen (NIPS, 2017)

Random Permutation Online Isotonic Regression. - Wojciech Kotlowski; Wouter M. Koolen; Alan Malek (NIPS, 2017)

Sequential Test for the Lowest Mean: From Thompson to Murphy Sampling. - Emilie Kaufmann; Wouter M. Koolen; Aurélien Garivier (NeurIPS, 2018)

Lipschitz Adaptivity with Multiple Learning Rates in Online Learning. - Zakaria Mhammedi; Wouter M. Koolen; Tim van Erven (COLT, 2019)

Efficient Algorithms for Minimax Decisions Under Tree-Structured Incompleteness. - Thijs van Ommen; Wouter M. Koolen; Peter D. Grünwald (ECSQARU, 2019)

Pure Exploration with Multiple Correct Answers. - Rémy Degenne; Wouter M. Koolen (NeurIPS, 2019)

Non-Asymptotic Pure Exploration by Solving Games. - Rémy Degenne; Wouter M. Koolen; Pierre Ménard (NeurIPS, 2019)

Open Problem: Fast and Optimal Online Portfolio Selection. - Tim van Erven; Dirk van der Hoeven; Wojciech Kotlowski; Wouter M. Koolen (COLT, 2020)

Lipschitz and Comparator-Norm Adaptivity in Online Learning. - Zakaria Mhammedi; Wouter M. Koolen (COLT, 2020)

Structure Adaptive Algorithms for Stochastic Bandits. - Rémy Degenne; Han Shao; Wouter M. Koolen (ICML, 2020)

Safe Testing. - Peter Grünwald; Rianne de Heide; Wouter M. Koolen (ITA, 2020)

Regret Minimization in Heavy-Tailed Bandits. - Shubhada Agrawal; Sandeep Juneja 001; Wouter M. Koolen (COLT, 2021)

Robust Online Convex Optimization in the Presence of Outliers. - Tim van Erven; Sarah Sachs; Wouter M. Koolen; Wojciech Kotlowski (COLT, 2021)

Optimal Best-Arm Identification Methods for Tail-Risk Measures. - Shubhada Agrawal; Wouter M. Koolen; Sandeep Juneja 001 (NeurIPS, 2021)

A/B/n Testing with Control in the Presence of Subpopulations. - Yoan Russac; Christina Katsimerou; Dennis Bohle; Olivier Cappé; Aurélien Garivier; Wouter M. Koolen (NeurIPS, 2021)

How can one test if a binary sequence is exchangeable? Fork-convex hulls, supermartingales, and Snell envelopes. - Aaditya Ramdas; Johannes Ruf; Martin Larsson; Wouter M. Koolen (CoRR, 2021)

MetaGrad: Adaptation using Multiple Learning Rates in Online Learning. - Tim van Erven; Wouter M. Koolen; Dirk van der Hoeven (J. Mach. Learn. Res., 2021)

Mixture Martingales Revisited with Applications to Sequential Tests and Confidence Intervals. - Emilie Kaufmann; Wouter M. Koolen (J. Mach. Learn. Res., 2021)

Luckiness in Multiscale Online Learning. - Wouter M. Koolen; Muriel Felipe Pérez-Ortiz (NeurIPS, 2022)

A composite generalization of Ville's martingale theorem. - Johannes Ruf; Martin Larsson; Wouter M. Koolen; Aaditya Ramdas (CoRR, 2022)

Log-optimal anytime-valid E-values. - Wouter M. Koolen; Peter Grünwald (Int. J. Approx. Reason., 2022)

Testing exchangeability: Fork-convexity, supermartingales and e-processes. - Aaditya Ramdas; Johannes Ruf; Martin Larsson; Wouter M. Koolen (Int. J. Approx. Reason., 2022)

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 (NeurIPS, 2023)

Hebbian learning inspired estimation of the linear regression parameters from queries. - Johannes Schmidt-Hieber; Wouter M. Koolen (CoRR, 2023)

Sequential learning of the Pareto front for multi-objective bandits. - Élise Crepon; Aurélien Garivier; Wouter M. Koolen (AISTATS, 2024)

On the Robustness of Kernel Ridge Regression Using the Cauchy Loss Function. - Hongwei Wen; Annika Betken; Wouter M. Koolen (CoRR, 2025)