Distributed learning is envisioned as the bedrock of next-generation intelligent networks,
where intelligent agents, such as mobile devices, robots, and sensors, exchange information …

The diffusion LMS algorithm has been extensively studied in recent years. This efficient
strategy allows to address distributed optimization problems over networks in the case …

Unlike traditional homogeneous single-task wireless sensor networks (WSNs),
heterogeneous and multitask WSNs allow the cooperation among multiple heterogeneous …

The problem of simultaneously learning several related tasks has received considerable
attention in several domains, especially in machine learning, with the so-called multitask …

In the case where the measurement noise involves impulsive interference, distributed
estimation algorithms based on the mean-square error (MSE) criterion may suffer from …

This paper studies the problem of data-adaptive representations for big, distributed data. It is
assumed that a number of geographically-distributed, interconnected sites have massive …

Over the last decade, differential privacy has achieved widespread adoption within the
privacy community. Moreover, it has attracted significant attention from the verification …

This paper examines a stochastic formulation of the generalized Nash equilibrium problem
where agents are subject to randomness in the environment of unknown statistical …

With the development of wireless sensor networks, many distributed algorithms have been
studied by researchers. This paper considers the situation of distributed estimation with false …

Multichannel active noise control (ANC) systems have been widely investigated for low-
frequency noise attenuation over a spatial region. Using a conventional centralized control …