Deep learning models have lately shown great performance in various fields such as
computer vision, speech recognition, speech translation, and natural language processing …

Real-world inverse synthetic aperture radar (ISAR) object recognition is a critical and
challenging problem in computer vision tasks. In this article, an efficient real-world ISAR …

A widespread folklore for explaining the success of Convolutional Neural Networks (CNNs)
is that CNNs use a more compact representation than the Fully-connected Neural Network …

Deep learning attempts medical image denoising either by directly learning the noise
present or via first learning the image content. We observe that residual learning (RL) often …

Convolutional analysis operator learning (CAOL) enables the unsupervised training of
(hierarchical) convolutional sparsifying operators or autoencoders from large datasets. One …

This thesis studies several theoretical problems in nonparametric statistics and machine
learning, mostly in the areas of nonparametric density functional estimation (estimating an …