The booming development of deep learning applications and services heavily relies on
large deep learning models and massive data in the cloud. However, cloud-based deep …

The ever-increasing layers and hyper-parameters of deep neural network are continuously
growing to generate large-scale network by training huge masses of data. However, it is …

Convolutional neural networks (CNNs) are commonly employed for demanding
applications, such as speech recognition, natural language processing, and computer …

Low precision deep neural network (DNN) training is one of the most effective techniques for
boosting DNNs' training efficiency, as it trims down the training cost from the finest bit level …

Modern iterations of deep learning models contain millions (billions) of unique parameters-
each represented by ab-bit number. Popular attempts at compressing neural networks (such …

Convolutional neural networks (CNNs) have shown good performance in many practical
applications. However, their high computational and storage requirements make them …

Summary Edge Artificial Intelligence (Edge AI) has become the buzzword for every industry
organization. Edge intelligence utilizes edge computing to access and analyze the data from …