With the development of Big data technology, data analysis has become
in...
Deep learning-based super-resolution models have the potential to
revolu...
Software built on top of machine learning algorithms is becoming increas...
This report addresses the technical aspects of de-identification of medi...
Candidate generation is the first stage in recommendation systems, where...
We propose an end-to-end trainable network that can simultaneously detec...
To understand the dynamics of optimization in deep neural networks, we
d...
Recent radiomic studies have witnessed promising performance of deep lea...
We present an extension to the Tacotron speech synthesis architecture th...
In this work, we propose "global style tokens" (GSTs), a bank of embeddi...
Progress in deep learning is slowed by the days or weeks it takes to tra...
Prosodic modeling is a core problem in speech synthesis. The key challen...
A text-to-speech synthesis system typically consists of multiple stages,...
We present a simple, general technique for reducing the sample complexit...
Kernel approximation using randomized feature maps has recently gained a...
Fourier PCA is Principal Component Analysis of a matrix obtained from hi...