The remarkable performance of deep Convolutional neural networks (CNNs) is generally
attributed to their deeper and wider architectures, which can come with significant …

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 …

The popularity of LLaMA (Touvron et al., 2023a; b) and other recently emerged moderate-
sized large language models (LLMs) highlights the potential of building smaller yet powerful …

With the widespread use of large artificial intelligence (AI) models such as ChatGPT, AI-
generated content (AIGC) has garnered increasing attention and is leading a paradigm shift …

Communication systems to date primarily aim at reliably communicating bit sequences.
Such an approach provides efficient engineering designs that are agnostic to the meanings …

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 …

As healthcare systems around the world face challenges such as escalating costs, limited
access, and growing demand for personalized care, artificial intelligence (AI) is emerging as …

Traffic prediction plays a crucial role in alleviating traffic congestion which represents a
critical problem globally, resulting in negative consequences such as lost hours of additional …

The next wave of wireless technologies is proliferating in connecting things among
themselves as well as to humans. In the era of the Internet of Things (IoT), billions of …

Real-world applications require the classification model to adapt to new classes without
forgetting old ones. Correspondingly, Class-Incremental Learning (CIL) aims to train a …