Advances in wired and wireless technology have necessitated the development of theory,
models, and tools to cope with the new challenges posed by large-scale control and …

Proliferation of low-cost, lightweight, and power efficient sensors and advances in networked
systems enable the employment of multiple sensors. Distributed estimation provides a …

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 …

We study nonconvex distributed optimization in multiagent networks with time-varying
(nonsymmetric) connectivity. We introduce the first algorithmic framework for the distributed …

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 …

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

We study the problem of distributed Kalman filtering and smoothing, where a set of nodes is
required to estimate the state of a linear dynamic system from in a collaborative manner. Our …

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 …