We propose an asynchronous, decentralized algorithm for consensus optimization. The
algorithm runs over a network in which the agents communicate with their neighbors and …

Diffusion networks where nodes collaboratively estimate the parameters of stochastic
models from shared observations and other estimates have become an established …

This paper formulates a multitask optimization problem where agents in the network have
individual objectives to meet, or individual parameter vectors to estimate, subject to a …

Modeling relations between local optimum parameter vectors to estimate in multitask
networks has attracted much attention over the last years. This work considers a distributed …

Combining diffusion strategies with complementary properties enables enhanced
performance when they can be run simultaneously. In this article, we first propose two …

Driven by the need to solve increasingly complex optimization problems in signal
processing and machine learning, recent years have seen rising interest in the behavior of …

The purpose of this article is to develop and study a decentralized strategy for Pareto
optimization of an aggregate cost consisting of regularized risks. Each risk is modeled as the …

Part I of this paper formulated a multitask optimization problem where agents in the network
have individual objectives to meet, or individual parameter vectors to estimate, subject to a …

The overview article [1] surveyed advances related to adaptation, learning, and optimization
over synchronous networks. Various distributed strategies were discussed that enable a …

Network virtualization has become pervasive and is used in many applications. Through the
combination of network virtualization and wireless sensor networks, it can greatly improve …