Publications

Sequential Learning

• Fast Best-in-Class Regret for Contextual Bandits
  Samuel Girard, Aurelien Bibaut, Arthur Gretton, Nathan Kallus, Houssam Zenati.
  Preprint, 2026.
  [Paper]

• Sequential Counterfactual Risk Minimization
  Houssam Zenati, Eustache Diemert, Matthieu Martin, Julien Mairal, Pierre Gaillard.
  ICML, 2023.
  [Paper] · [Code]

• Towards Efficient and Optimal Covariance-Adaptive Algorithms for Combinatorial Semi-Bandits
  Julien Zhou, Pierre Gaillard, Thibaud Rahier, Houssam Zenati, Julyan Arbel.
  NeurIPS, 2024.
  [Paper]

• Nested Bandits
  Matthieu Martin, Panagiotis Mertikopoulos, Thibaud Rahier, Houssam Zenati.
  ICML, 2022.
  [Paper] · [Code]

• Efficient Kernelized UCB for Contextual Bandits
  Houssam Zenati, Alberto Bietti, Eustache Diemert, Julien Mairal, Matthieu Martin, Pierre Gaillard.
  AISTATS, 2022.
  [Paper] · [Code]

• Optimistic Mirror Descent in Saddle-Point Problems: Going the Extra (Gradient) Mile
  Panagiotis Mertikopoulos, Bruno Lecouat, Houssam Zenati, Chuan-Sheng Foo, Vijay Chandrasekhar, Georgios Piliouras.
  ICLR, 2019.
  [Paper] · [Code]

Causal Inference

• Semiparametric Efficient Bilevel Gradient Estimation
  Fares El Khoury, Houssam Zenati, Nathan Kallus, Michael Arbel, Aurelien Bibaut.
  Preprint, 2026.

• Doubly Robust Proxy Causal Learning with Neural Mean Embeddings
  Bariscan Bozkurt, Alexandre Galashov, Dimitri Meunier, Zikai Shen, Arthur Gretton, Houssam Zenati.
  Preprint, 2026.
  [Paper]

• Semiparametric Efficient Test for Interpretable Distributional Treatment Effects
  Houssam Zenati, Arthur Gretton.
  Preprint, 2026.
  [Paper]

• Instrumental Variable Analysis Without Structural Equations
  Zikai Shen, Dimitri Meunier, Houssam Zenati, Arthur Gretton, Nathan Kallus, Aurelien Bibaut.
  Preprint, 2026.
  [Paper]

• Doubly-Robust Estimation of Counterfactual Policy Mean Embeddings
  Houssam Zenati, Bariscan Bozkurt, Arthur Gretton.
  NeurIPS, 2025.
  [Paper] · [Code]

• Double Debiased Machine Learning for Mediation Analysis with Continuous Treatments
  Houssam Zenati, Judith Abecassis, Julie Josse, Bertrand Thirion.
  AISTATS, 2025.
  [Paper] · [Code]

• Causal Mediation Analysis with One or Multiple Mediators: A Comparative Study
  Judith Abecassis, Houssam Zenati, Sami Boumaiza, Julie Josse, Bertrand Thirion.
  Psychological Methods, 2025.
  [Paper]

• Density Ratio-Free Doubly Robust Proxy Causal Learning
  Bariscan Bozkurt, Houssam Zenati, Dimitri Meunier, Liyuan Xu, Arthur Gretton.
  NeurIPS, 2025.
  [Paper] · [Code]

Inference under Adaptive Data Collection

• Efficient Inference after Directionally Stable Adaptive Experiments
  Zikai Shen, Houssam Zenati, Nathan Kallus, Arthur Gretton, Koulik Khamaru, Aurelien Bibaut.
  Preprint, 2026.
  [Paper]

• Kernel Treatment Effects with Adaptively Collected Data
  Houssam Zenati, Bariscan Bozkurt, Arthur Gretton.
  AISTATS, 2026.
  [Paper] · [Code]

Policy Learning from Logged and Redeployed Data

• Functional Natural Policy Gradients
  Aurelien Bibaut, Houssam Zenati, Thibaud Rahier, Nathan Kallus.
  Preprint, 2026.
  [Paper]

• Counterfactual Learning of Stochastic Policies with Continuous Actions
  Houssam Zenati, Alberto Bietti, Matthieu Martin, Eustache Diemert, Pierre Gaillard, Julien Mairal.
  Transactions on Machine Learning Research, 2025.
  [Paper] · [Code]

• Sequential Counterfactual Risk Minimization
  Houssam Zenati, Eustache Diemert, Matthieu Martin, Julien Mairal, Pierre Gaillard.
  ICML, 2023.
  [Paper] · [Code]

• Optimization Approaches for Counterfactual Risk Minimization with Continuous Actions
  Houssam Zenati, Alberto Bietti, Matthieu Martin, Eustache Diemert, Julien Mairal.
  ICLR Workshop on Causal Learning for Decision Making, 2020.
  [Paper] · [Code]

Deep Representation Learning

• Adversarially Learned Anomaly Detection
  Houssam Zenati, Manon Romain, Chuan-Sheng Foo, Bruno Lecouat, Vijay Chandrasekhar.
  ICDM, 2018.
  [Paper] · [Code]

• Efficient GAN-Based Anomaly Detection
  Houssam Zenati, Chuan-Sheng Foo, Bruno Lecouat, Gaurav Manek, Vijay Ramaseshan Chandrasekhar.
  ICLR Workshop, 2018.
  [Paper] · [Code]

• Semi-Supervised Learning with GANs: Revisiting Manifold Regularization
  Bruno Lecouat, Chuan-Sheng Foo, Houssam Zenati, Vijay Chandrasekhar.
  ICLR Workshop, 2018.
  [Paper] · [Code]

• Manifold Regularization with GANs for Semi-Supervised Learning
  Bruno Lecouat, Chuan-Sheng Foo, Houssam Zenati, Vijay Chandrasekhar.
  arXiv preprint, 2018.
  [Paper]

• Semi-Supervised Deep Learning for Abnormality Classification in Retinal Images
  Bruno Lecouat, Ken Chang, Chuan-Sheng Foo, Balagopal Unnikrishnan, James M. Brown, Houssam Zenati, Andrew Beers, Vijay Chandrasekhar, Jayashree Kalpathy-Cramer, Pavitra Krishnaswamy.
  NeurIPS Workshop on Machine Learning for Health, 2018.
  [Paper]

• Towards Practical Unsupervised Anomaly Detection on Retinal Images
  Khalil Ouardini, Huijuan Yang, Balagopal Unnikrishnan, Manon Romain, Camille Garcin, Houssam Zenati, J. Peter Campbell, Michael F. Chiang, Jayashree Kalpathy-Cramer, Vijay Chandrasekhar, and others.
  MICCAI Workshop on Domain Adaptation and Representation Transfer, 2019.
  [Paper]