3 papers
stat.ML2026
Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation
Andrea Basteri, Carlo Ciliberto, Alessandro Rudi
Missing values undermine statistical inference and machine learning pipelines, yet most imputation methods rely on heuristics or restrictive parametric assumptions that ignore the…
cs.LG2026
Lookahead identification in adversarial bandits: accuracy and memory bounds
Nataly Brukhim, Nicolò Cesa-Bianchi, Carlo Ciliberto
We study an identification problem in multi-armed bandits. In each round a learner selects one of arms and observes its reward, with the goal of eventually identifying an arm t…
cs.LG2024
Operator World Models for Reinforcement Learning
Pietro Novelli, Marco Pratticò, Massimiliano Pontil +1
Policy Mirror Descent (PMD) is a powerful and theoretically sound methodology for sequential decision-making. However, it is not directly applicable to Reinforcement Learning (RL)…