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Optimization Approaches for Counterfactual Risk Minimization with Continuous Actions


Apr 22, 2020
Houssam Zenati, Alberto Bietti, Matthieu Martin, Eustache Diemert, Julien Mairal

* ICLR 2020 Causal Learning for Decision Making Workshop 

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Semi-Supervised Deep Learning for Abnormality Classification in Retinal Images


Dec 19, 2018
Bruno Lecouat, Ken Chang, Chuan-Sheng Foo, Balagopal Unnikrishnan, James M. Brown, Houssam Zenati, Andrew Beers, Vijay Chandrasekhar, Jayashree Kalpathy-Cramer, Pavitra Krishnaswamy

* Machine Learning for Health (ML4H) Workshop at NeurIPS 2018 arXiv:1811.07216 

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Adversarially Learned Anomaly Detection


Dec 06, 2018
Houssam Zenati, Manon Romain, Chuan Sheng Foo, Bruno Lecouat, Vijay Ramaseshan Chandrasekhar

* In the Proceedings of the 20th IEEE International Conference on Data Mining (ICDM), 2018 

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


Oct 01, 2018
Panayotis Mertikopoulos, Bruno Lecouat, Houssam Zenati, Chuan-Sheng Foo, Vijay Chandrasekhar, Georgios Piliouras

* 26 pages, 14 figures 

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Manifold regularization with GANs for semi-supervised learning


Jul 11, 2018
Bruno Lecouat, Chuan-Sheng Foo, Houssam Zenati, Vijay Chandrasekhar


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Semi-Supervised Learning with GANs: Revisiting Manifold Regularization


May 23, 2018
Bruno Lecouat, Chuan-Sheng Foo, Houssam Zenati, Vijay R. Chandrasekhar

* Workshop track - ICLR 2018 
* Accepted paper 

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Efficient GAN-Based Anomaly Detection


Feb 17, 2018
Houssam Zenati, Chuan Sheng Foo, Bruno Lecouat, Gaurav Manek, Vijay Ramaseshan Chandrasekhar

* Submitted to the ICLR Workshop 2018 

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