Houssam Zenati

According to our database, Houssam Zenati authored at least 14 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Covariance-Adaptive Least-Squares Algorithm for Stochastic Combinatorial Semi-Bandits.

Julien Zhou, Pierre Gaillard, Thibaud Rahier, Houssam Zenati, Julyan Arbel

CoRR, 2024

2023

Sequential Counterfactual Risk Minimization.

Houssam Zenati, Eustache Diemert, Matthieu Martin, Julien Mairal, Pierre Gaillard

Proceedings of the International Conference on Machine Learning, 2023

2022

Efficient Kernel UCB for Contextual Bandits.

Houssam Zenati, Alberto Bietti, Eustache Diemert, Julien Mairal, Matthieu Martin, Pierre Gaillard

CoRR, 2022

Nested Bandits.

Matthieu Martin, Panayotis Mertikopoulos, Thibaud Rahier, Houssam Zenati

Proceedings of the International Conference on Machine Learning, 2022

Efficient Kernelized UCB for Contextual Bandits.

Houssam Zenati, Alberto Bietti, Eustache Diemert, Julien Mairal, Matthieu Martin, Pierre Gaillard

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2020

Optimization Approaches for Counterfactual Risk Minimization with Continuous Actions.

Houssam Zenati, Alberto Bietti, Matthieu Martin, Eustache Diemert, Julien Mairal

CoRR, 2020

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, Pavitra Krishnaswamy, Chuan-Sheng Foo

Proceedings of the Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data, 2019

Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile.

Panayotis Mertikopoulos, Bruno Lecouat, Houssam Zenati, Chuan-Sheng Foo, Vijay Chandrasekhar, Georgios Piliouras

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

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

CoRR, 2018

Manifold regularization with GANs for semi-supervised learning.

Bruno Lecouat, Chuan Sheng Foo, Houssam Zenati, Vijay 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, Georgios Piliouras

CoRR, 2018

Efficient GAN-Based Anomaly Detection.

Houssam Zenati, Chuan Sheng Foo, Bruno Lecouat, Gaurav Manek, Vijay Ramaseshan Chandrasekhar

CoRR, 2018

Semi-Supervised Learning With GANs: Revisiting Manifold Regularization.

Bruno Lecouat, Chuan Sheng Foo, Houssam Zenati, Vijay Ramaseshan Chandrasekhar

Proceedings of the 6th International Conference on Learning Representations, 2018

Adversarially Learned Anomaly Detection.

Houssam Zenati, Manon Romain, Chuan-Sheng Foo, Bruno Lecouat, Vijay Chandrasekhar

Proceedings of the IEEE International Conference on Data Mining, 2018