I am a final year PhD student at INRIA Thoth under the supervision of Julien Mairal and Pierre Gaillard. I also belong to the causal inference research group in the Criteo AI Lab. My research interests lie in the interface of counterfactual reasoning and online learning algorithms.
Prior to that, I received a M.Eng. degree in applied mathematics and computer science from CentraleSupelec as well as the MVA M.Sc. degree from ENS Paris-Saclay.
Previously, I also worked at the Institute for Infocomm Research under the supervision of Chuan-Sheng Foo and Vijay Chandrasekhar.
You can find my CV here.
I also like hiking, traveling and learning Japanese, as you may see here.
- May 2023: SCRM paper is accepted to ICML23!
- July 2022: I am attending ICML22 and will be presenting a poster, see you in Baltimore!
- July 2022: I am attending the EEML summer school in Lithuania, see you in Vilnius!
- Sequential Counterfactual Risk Minimization
- Houssam Zenati, Eustache Diemert, Matthieu Martin, Julien Mairal, Pierre Gaillard
- International Conference on Machine Learning, 2023
- Nested Bandits
- Matthieu Martin, Panagiotis Mertikopoulos, Thibaud Rahier, Houssam Zenati
- International Conference on Machine Learning, 2022
- Efficient Kernelized UCB for Contextual Bandits
- Houssam Zenati, Alberto Bietti, Eustache Diemert, Julien Mairal, Matthieu Martin, Pierre Gaillard
- International Conference on Artificial Intelligence and Statistics, 2022
- Counterfactual Learning of Stochastic Policies with Continuous Actions: from Models to Offline Evaluation
- Houssam Zenati, Alberto Bietti, Matthieu Martin, Eustache Diemert, Pierre Gaillard, Julien Mairal
- Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile
- Panagiotis Mertikopoulos, Bruno Lecouat, Houssam Zenati, Chuan-Sheng Foo, Vijay Chandrasekhar and Georgios Piliouras
- International Conference on Learning Representation, 2019
- Adversarially Learned Anomaly Detection
- Houssam Zenati, Manon Romain, Chuan-Sheng Foo, Bruno Lecouat, Vijay Chandrasekhar
- International Conference on Data Mining, 2019
- Optimization approaches for counterfactual risk minimization with continuous actions
- Houssam Zenati, Alberto Bietti, Matthieu Martin, Eustache Diemert, Julien Mairal
- International Conference on Learning Representation, Causal Learning for Decision Making Workshop, 2020
- 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, Pavitra Krishnaswamy, Chuan-Sheng Foo.
- International Conference on Medical Image
Computing and Computer Assisted Intervention Workshop, 2019
- Semi-Supervised Deep Learning for Abnormality Classification in Retinal Images
- Bruno Lecouat, Ken Chang, Chuan-Sheng Foo, Balagopal Unnikrishnan, James Brown, Houssam Zenati, Andrew Beers, Vijay Chandrasekhar, Jayashree Kalpathy-Cramer and Pavitra Krishnaswamy.
- Neural Information Processing Systems, ML4H Workshop 2018
- Semi-Supervised Learning With GANs: Revisiting Manifold Regularization
- Bruno Lecouat, Chuan Sheng Foo, Houssam Zenati, Vijay Chandrasekhar
- International Conference on Learning Representation Workshop, 2018
- Efficient GAN Based Anomaly Detection
- Houssam Zenati, Bruno Lecouat, Chuan Sheng Foo, Gaurav Manek, Vijay Chandrasekhar