Machine learning (ML) has succeeded in improving our daily routines by enabling
automation and improved decision making in a variety of industries such as healthcare …

Federated Learning is a much-needed technology in this golden era of big data and Artificial
Intelligence, due to its vital role in preserving data privacy, and eliminating the need to …

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 …

Every day, large amounts of sensitive data are distributed across mobile phones, wearable
devices, and other sensors. Traditionally, these enormous datasets have been processed on …

Over the past few years, personalized recommendations have emerged as a fundamental
component of the consumer electronics sector. The rise of decentralized federated learning …

Text-based person re-identification (ReID) has enabled canonical applications in searching
for and tracking targets from large-scale surveillance images with textual descriptions. Yet …

Since its introduction in 2016, researchers have applied the idea of Federated Learning (FL)
to several domains ranging from edge computing to banking. The technique's inherent …

Federated learning (FL) has been an area of active research in recent years. There have
been numerous studies in FL to make it more successful in the presence of data …

In the last few years, a very huge development has occurred in medical techniques using
artificial intelligence tools, especially in the diagnosis field. One of the essential things is …

Abstract The Artificial Intelligence of Things (AIoT), a combination of the Internet of Things
(IoT) and Artificial Intelligence (AI), plays an increasingly important role in smart agriculture …