In this paper, we define the general framework to describe the diffusion operators associated to a positive matrix. We define the equations associated to diffusion operators and present some general properties of their state vectors. We show how this can be applied to prove and improve the convergence of a fixed point problem associated to the matrix iteration scheme, including for distributed computation framework. The approach can be understood as a decomposition of the matrix-vector product operation in elementary operations at the vector entry level
Abstract—This paper investigates the problem of distributed stochastic approximation in multi-agent ...
Abstract cations, it is natural to consider distributed exe-We consider iterative algorithms of the ...
Abstract: Distributed averaging problems are a subclass of distributed consensus problems, which hav...
Part I of this paper developed the exact diffusion algorithm to remove the bias that is characterist...
We adopt an operator-theoretic perspective to study convergence of linear fixed-point iterations and...
We adopt an operator-theoretic perspective to study convergence of linear fixed-point iterations and...
This paper develops a distributed optimization strategy with guaranteed exact convergence for a broa...
Distributed optimization has been an extensively studied field for years. Recent developments in the...
The convergence analysis on the general iterative methods for the symmetric and positive semidefinit...
Asynchronous methods for solving systems of linear equations have been researched since Chazan and M...
Abstract — Consider a set of N agents seeking to solve dis-tributively the minimization problem infx...
AbstractWe continue the study of the convergence of dynamic iteration methods by applying them to li...
This paper presents new sufficient conditions for convergence and asymptotic or exponential stabilit...
AbstractWe develop the theory of convergence of a generic GR algorithm for the matrix eigenvalue pro...
We introduce novel convergence results for asynchronous iterations which appear in the analysis of p...
Abstract—This paper investigates the problem of distributed stochastic approximation in multi-agent ...
Abstract cations, it is natural to consider distributed exe-We consider iterative algorithms of the ...
Abstract: Distributed averaging problems are a subclass of distributed consensus problems, which hav...
Part I of this paper developed the exact diffusion algorithm to remove the bias that is characterist...
We adopt an operator-theoretic perspective to study convergence of linear fixed-point iterations and...
We adopt an operator-theoretic perspective to study convergence of linear fixed-point iterations and...
This paper develops a distributed optimization strategy with guaranteed exact convergence for a broa...
Distributed optimization has been an extensively studied field for years. Recent developments in the...
The convergence analysis on the general iterative methods for the symmetric and positive semidefinit...
Asynchronous methods for solving systems of linear equations have been researched since Chazan and M...
Abstract — Consider a set of N agents seeking to solve dis-tributively the minimization problem infx...
AbstractWe continue the study of the convergence of dynamic iteration methods by applying them to li...
This paper presents new sufficient conditions for convergence and asymptotic or exponential stabilit...
AbstractWe develop the theory of convergence of a generic GR algorithm for the matrix eigenvalue pro...
We introduce novel convergence results for asynchronous iterations which appear in the analysis of p...
Abstract—This paper investigates the problem of distributed stochastic approximation in multi-agent ...
Abstract cations, it is natural to consider distributed exe-We consider iterative algorithms of the ...
Abstract: Distributed averaging problems are a subclass of distributed consensus problems, which hav...