Showing stat.MLShow all
3 papers · 1 filter
stat.ML2025
Empirical PAC-Bayes Bounds for Markov Chains
Vahe Karagulyan, Pierre Alquier
The core of generalization theory was developed for independent observations. Some PAC and PAC-Bayes bounds are available for data that exhibit a temporal dependence. However, ther…
stat.ML2024
Minimax optimality of deep neural networks on dependent data via PAC-Bayes bounds
Pierre Alquier, William Kengne
In a groundbreaking work, Schmidt-Hieber (2020) proved the minimax optimality of deep neural networks with ReLu activation for least-square regression estimation over a large class…
stat.ML2024
Logarithmic Smoothing for Pessimistic Off-Policy Evaluation, Selection and Learning
Otmane Sakhi, Imad Aouali, Pierre Alquier +1
This work investigates the offline formulation of the contextual bandit problem, where the goal is to leverage past interactions collected under a behavior policy to evaluate, sele…