3 papers
cs.CV2018
Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models
Pouya Samangouei, Maya Kabkab, Rama Chellappa
In recent years, deep neural network approaches have been widely adopted for machine learning tasks, including classification. However, they were shown to be vulnerable to adversar…
cs.LG2018
Task-Aware Compressed Sensing with Generative Adversarial Networks
Maya Kabkab, Pouya Samangouei, Rama Chellappa
In recent years, neural network approaches have been widely adopted for machine learning tasks, with applications in computer vision. More recently, unsupervised generative models…
cs.CV2016
DCNNs on a Diet: Sampling Strategies for Reducing the Training Set Size
Maya Kabkab, Azadeh Alavi, Rama Chellappa
Large-scale supervised classification algorithms, especially those based on deep convolutional neural networks (DCNNs), require vast amounts of training data to achieve state-of-th…