In this paper, we study the problem of distributed multi-agent optimization over a network,
where each agent possesses a local cost function that is smooth and strongly convex. The …

Consider the consensus problem of minimizing f(x)=i=1^nf_i(x), where x∈R^p and each f_i
is only known to the individual agent i in a connected network of n agents. To solve this …

In this paper, we develop an interior-point method for solving a class of convex optimization
problems with time-varying objective and constraint functions. Using log-barrier penalty …

This paper considers a class of distributed quadratic optimization problem under an
undirected and connected graph. Different from most of the existing distributed optimization …

This paper develops the application of the alternating direction method of multipliers
(ADMM) to optimize a dynamic objective function in a decentralized multi-agent system. At …

This article focuses on an online version of the emerging distributed constrained
aggregative optimization framework, which is particularly suited for applications arising in …

The areas of machine learning and communication technology are converging. Today's
communications systems generate a huge amount of traffic data, which can help to …

This article deals with a network of computing agents aiming to solve an online optimization
problem in a distributed fashion, ie, by means of local computation and communication …

We propose an adaptive scheme for distributed learning of nonlinear functions by a network
of nodes. The proposed algorithm consists of a local adaptation stage utilizing multiple …

In distributed learning and optimization, a network of multiple computing units coordinates to
solve a large-scale problem. This article focuses on dynamic optimization over a …