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ORCIDHoussam Zenati
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2020 – today
- 2024
[i11]Julien Zhou, Pierre Gaillard, Thibaud Rahier, Houssam Zenati, Julyan Arbel:
Covariance-Adaptive Least-Squares Algorithm for Stochastic Combinatorial Semi-Bandits. CoRR abs/2402.15171 (2024)- 2023
- [c7]Houssam Zenati, Eustache Diemert, Matthieu Martin, Julien Mairal, Pierre Gaillard:
Sequential Counterfactual Risk Minimization. ICML 2023: 40681-40706 - [i10]Houssam Zenati, Eustache Diemert, Matthieu Martin, Julien Mairal, Pierre Gaillard:
Sequential Counterfactual Risk Minimization. CoRR abs/2302.12120 (2023) - 2022
- [c6]Houssam Zenati, Alberto Bietti, Eustache Diemert, Julien Mairal, Matthieu Martin, Pierre Gaillard:
Efficient Kernelized UCB for Contextual Bandits. AISTATS 2022: 5689-5720 - [c5]Matthieu Martin, Panayotis Mertikopoulos, Thibaud Rahier, Houssam Zenati:
Nested Bandits. ICML 2022: 15093-15121 - [i9]Houssam Zenati, Alberto Bietti, Eustache Diemert, Julien Mairal, Matthieu Martin, Pierre Gaillard:
Efficient Kernel UCB for Contextual Bandits. CoRR abs/2202.05638 (2022) - [i8]Matthieu Martin, Panayotis Mertikopoulos, Thibaud Rahier, Houssam Zenati:
Nested bandits. CoRR abs/2206.09348 (2022) - 2020
- [i7]Houssam Zenati, Alberto Bietti, Matthieu Martin, Eustache Diemert, Julien Mairal:
Optimization Approaches for Counterfactual Risk Minimization with Continuous Actions. CoRR abs/2004.11722 (2020)
2010 – 2019
- 2019
- [c4]Panayotis Mertikopoulos, Bruno Lecouat, Houssam Zenati, Chuan-Sheng Foo, Vijay Chandrasekhar, Georgios Piliouras:
Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile. ICLR (Poster) 2019 - [c3]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:
Towards Practical Unsupervised Anomaly Detection on Retinal Images. DART/MIL3ID@MICCAI 2019: 225-234 - 2018
- [c2]Houssam Zenati, Manon Romain, Chuan-Sheng Foo, Bruno Lecouat, Vijay Chandrasekhar:
Adversarially Learned Anomaly Detection. ICDM 2018: 727-736 - [c1]Bruno Lecouat, Chuan Sheng Foo, Houssam Zenati, Vijay Ramaseshan Chandrasekhar:
Semi-Supervised Learning With GANs: Revisiting Manifold Regularization. ICLR (Workshop) 2018 - [i6]Houssam Zenati, Chuan Sheng Foo, Bruno Lecouat, Gaurav Manek, Vijay Ramaseshan Chandrasekhar:
Efficient GAN-Based Anomaly Detection. CoRR abs/1802.06222 (2018) - [i5]Bruno Lecouat, Chuan Sheng Foo, Houssam Zenati, Vijay Ramaseshan Chandrasekhar:
Semi-Supervised Learning with GANs: Revisiting Manifold Regularization. CoRR abs/1805.08957 (2018) - [i4]Panayotis Mertikopoulos, Houssam Zenati, Bruno Lecouat, Chuan-Sheng Foo, Vijay Chandrasekhar, Georgios Piliouras:
Mirror descent in saddle-point problems: Going the extra (gradient) mile. CoRR abs/1807.02629 (2018) - [i3]Bruno Lecouat, Chuan Sheng Foo, Houssam Zenati, Vijay Chandrasekhar:
Manifold regularization with GANs for semi-supervised learning. CoRR abs/1807.04307 (2018) - [i2]Houssam Zenati, Manon Romain, Chuan Sheng Foo, Bruno Lecouat, Vijay Ramaseshan Chandrasekhar:
Adversarially Learned Anomaly Detection. CoRR abs/1812.02288 (2018) - [i1]Bruno Lecouat, Ken Chang, Chuan-Sheng Foo, Balagopal Unnikrishnan, James M. Brown, Houssam Zenati, Andrew Beers, Vijay Chandrasekhar, Jayashree Kalpathy-Cramer, Pavitra Krishnaswamy:
Semi-Supervised Deep Learning for Abnormality Classification in Retinal Images. CoRR abs/1812.07832 (2018)
Coauthor Index
aka: Vijay Ramaseshan Chandrasekhar
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