In this work, we identify the inefficiency in widely used allreduce algorithms, and the opportunity of algorithm-architecture co-design. We propose MULTITREE all-reduce algorithm with topology and ...

This article explores some of the most influential deep learning architectures: Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Generative Adversarial Networks (GANs), ...

Implement basic-to-advanced deep learning algorithms; Master the mathematics behind deep learning algorithms; Become familiar with gradient descent and its variants, such as AMSGrad, AdaDelta, Adam, ...

Deep learning (DL) is playing an increasingly important role in our lives. It has already made a huge impact in areas, such as cancer diagnosis, precision medicine, self-driving cars, predictive ...

In the past few years, Neural Architecture Search (NAS) is an attractive technique that promised automatic design for high-performance neural networks. However, NAS methods considerably vary in search ...

Deep learning defined. Deep learning is a form of machine learning that models patterns in data as complex, multi-layered networks. Because deep learning is the most general way to model a problem ...