Adversarially Learned Anomaly Detection. - Houssam Zenati; Manon Romain; Chuan-Sheng Foo; Bruno Lecouat; Vijay Chandrasekhar 001 (ICDM, 2018)

Semi-Supervised Learning With GANs: Revisiting Manifold Regularization. - Bruno Lecouat; Chuan Sheng Foo; Houssam Zenati; Vijay Ramaseshan Chandrasekhar (ICLR (Workshop), 2018)

Efficient GAN-Based Anomaly Detection. - Houssam Zenati; Chuan Sheng Foo; Bruno Lecouat; Gaurav Manek; Vijay Ramaseshan Chandrasekhar (CoRR, 2018)

Mirror descent in saddle-point problems: Going the extra (gradient) mile. - Panayotis Mertikopoulos; Houssam Zenati; Bruno Lecouat; Chuan-Sheng Foo; Vijay Chandrasekhar 001; Georgios Piliouras (CoRR, 2018)

Manifold regularization with GANs for semi-supervised learning. - Bruno Lecouat; Chuan Sheng Foo; Houssam Zenati; Vijay Chandrasekhar 001 (CoRR, 2018)

Semi-Supervised Deep Learning for Abnormality Classification in Retinal Images. - Bruno Lecouat; Ken Chang; Chuan-Sheng Foo; Balagopal Unnikrishnan; James M. Brown 001; Houssam Zenati; Andrew Beers; Vijay Chandrasekhar 001; Jayashree Kalpathy-Cramer; Pavitra Krishnaswamy (CoRR, 2018)

Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile. - Panayotis Mertikopoulos; Bruno Lecouat; Houssam Zenati; Chuan-Sheng Foo; Vijay Chandrasekhar 001; Georgios Piliouras (ICLR (Poster), 2019)

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 001; Pavitra Krishnaswamy; Chuan-Sheng Foo (DART/MIL3ID@MICCAI, 2019)

Optimization Approaches for Counterfactual Risk Minimization with Continuous Actions. - Houssam Zenati; Alberto Bietti; Matthieu Martin; Eustache Diemert; Julien Mairal (CoRR, 2020)

Efficient Kernelized UCB for Contextual Bandits. - Houssam Zenati; Alberto Bietti; Eustache Diemert; Julien Mairal; Matthieu Martin; Pierre Gaillard (AISTATS, 2022)

Nested Bandits. - Matthieu Martin; Panayotis Mertikopoulos; Thibaud Rahier; Houssam Zenati (ICML, 2022)

Efficient Kernel UCB for Contextual Bandits. - Houssam Zenati; Alberto Bietti; Eustache Diemert; Julien Mairal; Matthieu Martin; Pierre Gaillard (CoRR, 2022)

Sequential Counterfactual Risk Minimization. - Houssam Zenati; Eustache Diemert; Matthieu Martin; Julien Mairal; Pierre Gaillard (ICML, 2023)

Towards Efficient and Optimal Covariance-Adaptive Algorithms for Combinatorial Semi-Bandits. - Julien Zhou; Pierre Gaillard; Thibaud Rahier; Houssam Zenati; Julyan Arbel (NeurIPS, 2024)

Covariance-Adaptive Least-Squares Algorithm for Stochastic Combinatorial Semi-Bandits. - Julien Zhou; Pierre Gaillard; Thibaud Rahier; Houssam Zenati; Julyan Arbel (CoRR, 2024)

Double Debiased Machine Learning for Mediation Analysis with Continuous Treatments. - Houssam Zenati; Judith Abécassis; Julie Josse; Bertrand Thirion (AISTATS, 2025)

Counterfactual Learning of Stochastic Policies with Continuous Actions. - Houssam Zenati; Alberto Bietti; Matthieu Martin; Eustache Diemert; Pierre Gaillard; Julien Mairal (Trans. Mach. Learn. Res., 2025)

Density Ratio-Free Doubly Robust Proxy Causal Learning. - Bariscan Bozkurt; Houssam Zenati; Dimitri Meunier; Liyuan Xu; Arthur Gretton (CoRR, 2025)

Doubly-Robust Estimation of Counterfactual Policy Mean Embeddings. - Houssam Zenati; Bariscan Bozkurt; Arthur Gretton (CoRR, 2025)