30 citations · 30 across the 2 of their papers we have counts for
7 papers
Efficient Kernel UCB for Contextual Bandits
Houssam Zenati, Alberto Bietti, Eustache Diemert +3
In this paper, we tackle the computational efficiency of kernelized UCB algorithms in contextual bandits. While standard methods require a O(CT^3) complexity where T is the horizon…
Semi-Supervised Deep Learning for Abnormality Classification in Retinal Images
Bruno Lecouat, Ken Chang, Chuan-Sheng Foo +7
Supervised deep learning algorithms have enabled significant performance gains in medical image classification tasks. But these methods rely on large labeled datasets that require…
Adversarially Learned Anomaly Detection
Houssam Zenati, Manon Romain, Chuan Sheng Foo +2
Anomaly detection is a significant and hence well-studied problem. However, developing effective anomaly detection methods for complex and high-dimensional data remains a challenge…
Manifold regularization with GANs for semi-supervised learning
Bruno Lecouat, Chuan-Sheng Foo, Houssam Zenati +1
Generative Adversarial Networks are powerful generative models that are able to model the manifold of natural images. We leverage this property to perform manifold regularization b…
Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile
Panayotis Mertikopoulos, Bruno Lecouat, Houssam Zenati +3
Owing to their connection with generative adversarial networks (GANs), saddle-point problems have recently attracted considerable interest in machine learning and beyond. By necess…
Semi-Supervised Learning with GANs: Revisiting Manifold Regularization
Bruno Lecouat, Chuan-Sheng Foo, Houssam Zenati +1
GANS are powerful generative models that are able to model the manifold of natural images. We leverage this property to perform manifold regularization by approximating the Laplaci…