6 papers
Optimized projection-free algorithms for online learning: construction and worst-case analysis
Julien Weibel, Pierre Gaillard, Wouter M. Koolen +1
This work studies and develop projection-free algorithms for online learning with linear optimization oracles (a.k.a. Frank-Wolfe) for handling the constraint set. More precisely,…
On the Robustness of Kernel Ridge Regression Using the Cauchy Loss Function
Hongwei Wen, Annika Betken, Wouter Koolen
Robust regression aims to develop methods for estimating an unknown regression function in the presence of outliers, heavy-tailed distributions, or contaminated data, which can sev…
A Generalisation of Ville's Inequality to Monotonic Lower Bounds and Thresholds
Wouter M. Koolen, Muriel Felipe Pérez-Ortiz, Tyron Lardy
Essentially all anytime-valid methods hinge on Ville's inequality to gain validity across time without incurring a union bound. Ville's inequality is a proper generalisation of Mar…
Accelerated Mirror Descent for Non-Euclidean Star-convex Functions
Clement Lezane, Sophie Langer, Wouter M Koolen
Acceleration for non-convex functions is a fundamental challenge in optimisation. We revisit star-convex functions, which are strictly unimodal on all lines through a minimizer. [1…
Supermartingales for One-Sided Tests: Sufficient Monotone Likelihood Ratios are Sufficient
Peter D. Grünwald, Wouter M. Koolen
The t-statistic is a widely-used scale-invariant statistic for testing the null hypothesis that the mean is zero. Martingale methods enable sequential testing with the t-statistic…
Sequential Learning of the Pareto Front for Multi-objective Bandits
Elise Crépon, Aurélien Garivier, Wouter M Koolen
We study the problem of sequential learning of the Pareto front in multi-objective multi-armed bandits. An agent is faced with K possible arms to pull. At each turn she picks one,…