2 papers
stat.ML2026
Self-Concordant Perturbations for Linear Bandits
Lucas Lévy, Jean-Lou Valeau, Arya Akhavan +1
We consider the adversarial linear bandits setting and present a unified algorithmic framework that bridges Follow-the-Regularized-Leader (FTRL) and Follow-the-Perturbed-Leader (FT…
stat.ML2025
Non-stationary Bandit Convex Optimization: A Comprehensive Study
Xiaoqi Liu, Dorian Baudry, Julian Zimmert +2
Bandit Convex Optimization is a fundamental class of sequential decision-making problems, where the learner selects actions from a continuous domain and observes a loss (but not it…