This paper surveys recent advances related to adaptation, learning, and optimization over
networks. Various distributed strategies are discussed that enable a collection of networked …

This paper reviews signal processing research for applications in the future electric power
grid, commonly referred to as smart grid. Generally, it is expected that the grid of the future …

In decentralized optimization, nodes cooperate to minimize an overall objective function that
is the sum (or average) of per-node private objective functions. Algorithms interleave local …

This work deals with the topic of information processing over graphs. The presentation is
largely self-contained and covers results that relate to the analysis and design of multi-agent …

We propose an adaptive diffusion mechanism to optimize global cost functions in a
distributed manner over a network of nodes. The cost function is assumed to consist of a …

Wireless sensor networks (WSNs) are extensively adopted for remote monitoring and
tracking scenarios, such as battlefield surveillance, target detection and tracking, traffic …

Nature provides splendid examples of real-time learning and adaptation behavior that
emerges from highly localized interactions among agents of limited capabilities. For …

Adaptive networks are well-suited to perform decentralized information processing and
optimization tasks and to model various types of self-organized and complex behavior …

Adaptive networks consist of a collection of nodes with adaptation and learning abilities. The
nodes interact with each other on a local level and diffuse information across the network to …

This paper develops a distributed optimization strategy with guaranteed exact convergence
for a broad class of left-stochastic combination policies. The resulting exact diffusion strategy …