Deep Learning has recently been gaining popularity. From the micro-architecture field to the
upper-layer end applications, a lot of research work has been proposed in the literature to …

Recently, deep learning has become one of the most disruptive trends in the technology
world. Deep learning techniques are increasingly achieving significant results in different …

Strong empirical evidence that one machine-learning algorithm A outperforms another one
B, ideally calls for multiple trials optimizing the learning pipeline over sources of variation …

Deep learning belongs to the field of artificial intelligence, where machines perform tasks
that typically require some kind of human intelligence. Deep learning tries to achieve this by …

The software described in this document is furnished under a license agreement. The
software may be used or copied only under the terms of the license agreement. No part of …

We introduce Deep500: the first customizable benchmarking infrastructure that enables fair
comparison of the plethora of deep learning frameworks, algorithms, libraries, and …

Selecting an optimizer is a central step in the contemporary deep learning pipeline. In this
paper, we demonstrate the sensitivity of optimizer comparisons to the hyperparameter tuning …

One of the essential components of deep learning is the choice of the loss function and
performance metrics used to train and evaluate models. This paper reviews the most …

Deep Learning (DL) is one of the hottest trends in machine learning as DL approaches
produced results superior to the state-of-the-art in problematic areas such as image …

The current Deep Learning (DL) landscape is fast-paced and is rife with non-uniform
models, hardware/software (HW/SW) stacks. Currently, there is no DL benchmarking …