Houssam Zenati

28 papers A* 4A 2Journal 19Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Efficient Inference after Directionally Stable Adaptive Experiments. CoRR Zikai Shen, Houssam Zenati, Nathan Kallus, Arthur Gretton, Koulik Khamaru, Aurélien Bibaut
2026	J	`jnl`	Functional Natural Policy Gradients. CoRR Aurélien F. Bibaut, Houssam Zenati, Thibaud Rahier, Nathan Kallus
2025	J	`jnl`	Counterfactual Learning of Stochastic Policies with Continuous Actions. Trans. Mach. Learn. Res. Houssam Zenati, Alberto Bietti, Matthieu Martin, Eustache Diemert, Pierre Gaillard, Julien Mairal
2025	J	`jnl`	Density Ratio-Free Doubly Robust Proxy Causal Learning. CoRR Bariscan Bozkurt, Houssam Zenati, Dimitri Meunier, Liyuan Xu, Arthur Gretton
2025	A	`conf`	Double Debiased Machine Learning for Mediation Analysis with Continuous Treatments. AISTATS Houssam Zenati, Judith Abécassis, Julie Josse, Bertrand Thirion
2025	J	`jnl`	Double Debiased Machine Learning for Mediation Analysis with Continuous Treatments. CoRR Houssam Zenati, Judith Abécassis, Julie Josse, Bertrand Thirion
2025	J	`jnl`	Doubly-Robust Estimation of Counterfactual Policy Mean Embeddings. CoRR Houssam Zenati, Bariscan Bozkurt, Arthur Gretton
2025	J	`jnl`	Kernel Treatment Effects with Adaptively Collected Data. CoRR Houssam Zenati, Bariscan Bozkurt, Arthur Gretton
2025	J	`jnl`	Online Policy Learning via a Self-Normalized Maximal Inequality. CoRR Samuel Girard, Aurélien Bibaut, Houssam Zenati
2024	J	`jnl`	Covariance-Adaptive Least-Squares Algorithm for Stochastic Combinatorial Semi-Bandits. CoRR Julien Zhou, Pierre Gaillard, Thibaud Rahier, Houssam Zenati, Julyan Arbel
2024	A*	`conf`	Towards Efficient and Optimal Covariance-Adaptive Algorithms for Combinatorial Semi-Bandits. NeurIPS Julien Zhou, Pierre Gaillard, Thibaud Rahier, Houssam Zenati, Julyan Arbel
2023	A*	`conf`	Sequential Counterfactual Risk Minimization. ICML Houssam Zenati, Eustache Diemert, Matthieu Martin, Julien Mairal, Pierre Gaillard
2023	J	`jnl`	Sequential Counterfactual Risk Minimization. CoRR Houssam Zenati, Eustache Diemert, Matthieu Martin, Julien Mairal, Pierre Gaillard
2022	J	`jnl`	Efficient Kernel UCB for Contextual Bandits. CoRR Houssam Zenati, Alberto Bietti, Eustache Diemert, Julien Mairal, Matthieu Martin, Pierre Gaillard
2022	A	`conf`	Efficient Kernelized UCB for Contextual Bandits. AISTATS Houssam Zenati, Alberto Bietti, Eustache Diemert, Julien Mairal, Matthieu Martin, Pierre Gaillard
2022	A*	`conf`	Nested Bandits. ICML Matthieu Martin, Panayotis Mertikopoulos, Thibaud Rahier, Houssam Zenati
2022	J	`jnl`	Nested bandits. CoRR Matthieu Martin, Panayotis Mertikopoulos, Thibaud Rahier, Houssam Zenati
2020	J	`jnl`	Optimization Approaches for Counterfactual Risk Minimization with Continuous Actions. CoRR Houssam Zenati, Alberto Bietti, Matthieu Martin, Eustache Diemert, Julien Mairal
2019	—	`conf`	Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile. ICLR (Poster) Panayotis Mertikopoulos, Bruno Lecouat, Houssam Zenati, Chuan-Sheng Foo, Vijay Chandrasekhar, Georgios Piliouras
2019	—	`conf`	Towards Practical Unsupervised Anomaly Detection on Retinal Images. DART/MIL3ID@MICCAI Khalil Ouardini, Huijuan Yang, Balagopal Unnikrishnan, Manon Romain, Camille Garcin, Houssam Zenati, J. Peter Campbell, Michael F. Chiang, Jayashree Kalpathy-Cramer, Vijay Chandrasekhar, Pavitra Krishnaswamy, Chuan-Sheng Foo
2018	A*	`conf`	Adversarially Learned Anomaly Detection. ICDM Houssam Zenati, Manon Romain, Chuan-Sheng Foo, Bruno Lecouat, Vijay Chandrasekhar
2018	J	`jnl`	Adversarially Learned Anomaly Detection. CoRR Houssam Zenati, Manon Romain, Chuan Sheng Foo, Bruno Lecouat, Vijay Ramaseshan Chandrasekhar
2018	J	`jnl`	Efficient GAN-Based Anomaly Detection. CoRR Houssam Zenati, Chuan Sheng Foo, Bruno Lecouat, Gaurav Manek, Vijay Ramaseshan Chandrasekhar
2018	J	`jnl`	Manifold regularization with GANs for semi-supervised learning. CoRR Bruno Lecouat, Chuan Sheng Foo, Houssam Zenati, Vijay Chandrasekhar
2018	J	`jnl`	Mirror descent in saddle-point problems: Going the extra (gradient) mile. CoRR Panayotis Mertikopoulos, Houssam Zenati, Bruno Lecouat, Chuan-Sheng Foo, Vijay Chandrasekhar, Georgios Piliouras
2018	J	`jnl`	Semi-Supervised Deep Learning for Abnormality Classification in Retinal Images. CoRR Bruno Lecouat, Ken Chang, Chuan-Sheng Foo, Balagopal Unnikrishnan, James M. Brown, Houssam Zenati, Andrew Beers, Vijay Chandrasekhar, Jayashree Kalpathy-Cramer, Pavitra Krishnaswamy
2018	—	`conf`	Semi-Supervised Learning With GANs: Revisiting Manifold Regularization. ICLR (Workshop) Bruno Lecouat, Chuan Sheng Foo, Houssam Zenati, Vijay Ramaseshan Chandrasekhar
2018	J	`jnl`	Semi-Supervised Learning with GANs: Revisiting Manifold Regularization. CoRR Bruno Lecouat, Chuan Sheng Foo, Houssam Zenati, Vijay Ramaseshan Chandrasekhar