activity
20182026
most citedEfficient GAN-Based Anomaly Detection

482 citations · 677 across the 19 of their papers we have counts for

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Showing 2025Show all

6 papers · 1 filter

stat.ML2025

Fast Best-in-Class Regret for Contextual Bandits

Samuel Girard, Aurelien Bibaut, Arthur Gretton +2

We study the problem of stochastic contextual bandits in the agnostic setting, where the goal is to compete with the best policy in a given class without assuming realizability or…

stat.ML2025

Kernel Treatment Effects with Adaptively Collected Data

Houssam Zenati, Bariscan Bozkurt, Arthur Gretton

Adaptive experiments improve efficiency by adjusting treatment assignments based on past outcomes, but this adaptivity breaks the i.i.d.\ assumptions that underpin classical asympt…

stat.ML2025

Doubly-Robust Estimation of Counterfactual Policy Mean Embeddings

Houssam Zenati, Bariscan Bozkurt, Arthur Gretton

Estimating the distribution of outcomes under counterfactual policies is critical for decision-making in domains such as recommendation, advertising, and healthcare. We propose and…

stat.AP2025

Causal mediation analysis with one or multiple mediators: a comparative study

Judith Abécassis, Houssam Zenati, Sami Boumaïza +2

Mediation analysis breaks down the causal effect of a treatment on an outcome into an indirect effect, acting through a third group of variables called mediators, and a direct effe…

cs.LG2025

Density Ratio-Free Doubly Robust Proxy Causal Learning

Bariscan Bozkurt, Houssam Zenati, Dimitri Meunier +2

We study the problem of causal function estimation in the Proxy Causal Learning (PCL) framework, where confounders are not observed but proxies for the confounders are available. T…

stat.ML2025

Double Debiased Machine Learning for Mediation Analysis with Continuous Treatments

Houssam Zenati, Judith Abécassis, Julie Josse +1

Uncovering causal mediation effects is of significant value to practitioners seeking to isolate the direct treatment effect from the potential mediated effect. We propose a double…