With advances in AI (Artificial Intelligence) and the surge of Big Data, Deep learning (DL)
has a remarkable impact on businesses in various domains including finance, marketing …

The computing wall and data movement challenges of deep neural networks (DNNs) have
exposed the limitations of conventional CMOS-based DNN accelerators. Furthermore, the …

Abstract Deep Learning as a Service (DLaaS) is rapidly developing recently to enable
applications including self-driving, face recognition, and natural language processing for …

Machine learning has shown tremendous benefits in solving complex network problems and
providing situation and parameter prediction. However, heavy resources are required to …

Recently, Deep Convolutional Neural Network (DCNN) has achieved tremendous success
in many machine learning applications. Nevertheless, the deep structure has brought …

Multi-task learning provides plenty of room for performance improvement to single-task
learning, when learned tasks are related and learned with mutual information. In this work …

Abstract Machine learning has become increasingly popular in recent years. Due to the high
accuracy and excellent scalability, deep neural networks have emerged as a fundamental …

The Internet-of-Things (IoT) is an interconnected and distributed network of devices or
objects that exchange information through wired or wireless communications. These …

The use of graph applications is common in many areas; however, irregular and data-driven
memory access patterns combined with the large sizes of graph data results in performance …

The Internet of Things (IoT) is a key enabler for many future wireless applications, from
manufacturing to healthcare. The IoT interconnects many objects (or devices) that perform …