This paper develops a fully distributed differentially-private learning algorithm based on the alternating direction method of multipliers (ADMM) to solve nonsmooth optimization problems. We employ an approximation of the ...

We propose a privacy-preserving distributed maximum consensus algorithm where the local state of the agents and identity of the maximum state owner is kept private from adversaries. To that end, we reformulate the maximum ...

This article presents a unified framework for filtering and control of quaternion-valued state vector processes through multiagent networked systems. To achieve this goal, the filtering problem in sensor networks is ...

Cervical cancer screening programs have reduced the incidence of cervical cancer, but suffer from over- and too infrequent screening as women’s risk of developing cervical cancer differs. Personalized risk prediction models ...

Many assumptions in the federated learning literature present a best-case scenario that can not be satisfied in most real-world applications. An asynchronous setting reflects the realistic environment in which federated ...

Internet of Things technologies will enable smart energy planning, which in turn will expedite the adoption of renewable energy (RE). In this paper, we propose a mathematical framework to optimize the use of RE in a shared ...

Wireless sensor networks (WSN) provide a versatile monitoring infrastructure to track physical processes for autonomous and manual decision-making. In WSN and wireless networked control systems, sensors observe physical ...