As the computing paradigm shifts from cloud computing to end-edge-cloud computing, it
also supports artificial intelligence evolving from a centralized manner to a distributed one …

Ubiquitous sensors and smart devices from factories and communities are generating
massive amounts of data, and ever-increasing computing power is driving the core of …

Deep learning is currently widely used in a variety of applications, including computer vision
and natural language processing. End devices, such as smartphones and Internet-of-Things …

With the breakthroughs in deep learning, the recent years have witnessed a booming of
artificial intelligence (AI) applications and services, spanning from personal assistant to …

The Internet of Things (IoT) has created a ubiquitously connected world powered by a
multitude of wired and wireless sensors generating a variety of heterogeneous data over …

Successful integration of deep neural networks (DNNs) or deep learning (DL) has resulted
in breakthroughs in many areas. However, deploying these highly accurate models for data …

In a few years, the world will be populated by billions of connected devices that will be
placed in our homes, cities, vehicles, and industries. Devices with limited resources will …

Despite the soaring use of convolutional neural networks (CNNs) in mobile applications,
uniformly sustaining high-performance inference on mobile has been elusive due to the …

The rapid uptake of mobile devices and the rising popularity of mobile applications and
services pose unprecedented demands on mobile and wireless networking infrastructure …

While" instruction-tuned" generative large language models (LLMs) have demonstrated an
impressive ability to generalize to new tasks, the training phases heavily rely on large …