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20242026
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stat.ML2026

Nonparametric Instrumental Variable Analysis Without Structural Equations: Debiased Inference on Functionals of Inverse Problems with No Solutions

Zikai Shen, Nathan Kallus, Dimitri Meunier +3

We consider debiased inference on finite-dimensional functionals of infinite-dimensional least-squares solutions to inverse problems as a way to avoid having to assume exact soluti…

stat.ML2026

Functional Natural Policy Gradients

Aurelien Bibaut, Houssam Zenati, Thibaud Rahier +1

We propose a cross-fitted debiasing device for policy learning from offline data. A key consequence of the resulting learning principle is regret even for policy classes…

stat.ML2026

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.ML2026

Efficient Inference after Directionally Stable Adaptive Experiments

Zikai Shen, Houssam Zenati, Nathan Kallus +3

We study inference on scalar-valued pathwise differentiable targets after adaptive data collection, such as a bandit algorithm. We introduce a novel target-specific condition, dire…

stat.ML2025

Semiparametric Double Reinforcement Learning with Applications to Long-Term Causal Inference

Lars van der Laan, David Hubbard, Allen Tran +3

Double reinforcement learning (DRL) provides efficient off-policy inference for policy values in nonparametric Markov decision processes (MDPs), but fully nonparametric estimators…