This paper explores the potential for communication-efficient federated learning (FL) in
modern distributed systems. FL is an emerging distributed machine learning technique that …

Secure aggregation consists of computing the sum of data collected from multiple sources
without disclosing these individual inputs. Secure aggregation has been found useful for …

In the evolving landscape of Open Radio Access Networks (Open RAN), the dynamic and
unpredictable nature of network conditions presents significant challenges for traditional …

Federated learning addresses the issue of sensitive training data in centralized machine
learning to a certain extent. However, it may introduce new privacy risks due to model …

Nowadays, the proliferation of handheld devices embedded with multiple mobile sensors
and the growth of fast communication and data processing technologies have contributed to …

The Internet of Things (IoT) is one of the most important technologies in our current world. It
is composed of connected devices with sensors and processing abilities, all connected to a …