Survival analysis is a fundamental tool in medicine, modeling the time until an event of
interest occurs in a population. However, in real-world applications, survival data are often …

In the realm of liver transplantation, accurately determining hepatic steatosis levels is crucial.
Recognizing the essential need for improved diagnostic precision, particularly for optimizing …

Federated Learning (FL) represents a paradigm shift in the field of machine learning,
offering an approach for a decentralized training of models across a multitude of devices …

In today's world, the rapid expansion of IoT networks and the proliferation of smart devices in
our daily lives, have resulted in the generation of substantial amounts of heterogeneous …

In the realm of Federated Learning (FL), particularly within the manufacturing sector, the
strategy for selecting client weights for server aggregation is pivotal for model performance …

Federated learning (FL) is a key solution for datadriven the Artificial Intelligence of Things
(AIoT). Although much progress has been made, scalability remains a core challenge for …

Unmanned aerial vehicles (UAVs) can be used as drones' edge Intelligence to assist with
data collection, training models, and communication over wireless networks. UAV use for …

Despite achieving good performance and wide adoption, machine learning based security
detection models (eg, malware classifiers) are subject to concept drift and evasive evolution …

Federated Learning (FL) enables distributed machine learning model training on edge
devices, ensuring data privacy [1, 2]. However, managing such training with the devices' …

JavaScript (JS) is one of the most used programming languages for mobile applications. As
JS is increasingly used in computation-intensive and latency-sensitive components, JS …