Abstract—This paper presents explicit convergence rates for a class of deterministic distributed augmented Lagrangian methods. The expressions for the convergence rates show the dependence on the underlying network parameters. Simulations illustrate the analytical results. Index Terms—distributed optimization, linear convergence rate, augmented Lagrangian, consensus. I
Abstract — Consider a set of N agents seeking to solve dis-tributively the minimization problem infx...
We study distributed optimization in networked systems, where nodes cooperate to find the optimal qu...
This paper gives a lower bound on the convergence rate of a class of network consensus algorithms. T...
We study distributed optimization where nodes cooperatively minimize the sum of their individual, lo...
Abstract—We study distributed optimization where nodes co-operatively minimize the sum of their indi...
Abstract We propose a novel distributed method for convex optimization problems with a certain separ...
A multi-agent optimization problem motivated by the management of energy systems is discussed. The a...
Abstract — In this paper, we propose a distributed algorithm for optimal routing in wireless multi-h...
Ce talk est un des trois "exposés phares" invités par Olivier BeaumontNational audienceLarge scale d...
International audienceIn this article, we illustrate practical issues arising in the development of ...
A multi-agent optimization problem motivated by the management of energy systems is discussed. The a...
We study the convergence speed of distributed iterative algorithms for the consensus and averaging p...
We propose three new algorithms for the distributed averaging and consensus prob-lems: two for the f...
In this paper, we compare six known linear distributed average consensus algorithms on a sensor netw...
This paper presents an empirical study of the convergence characteristics of augmented Lagrangian co...
Abstract — Consider a set of N agents seeking to solve dis-tributively the minimization problem infx...
We study distributed optimization in networked systems, where nodes cooperate to find the optimal qu...
This paper gives a lower bound on the convergence rate of a class of network consensus algorithms. T...
We study distributed optimization where nodes cooperatively minimize the sum of their individual, lo...
Abstract—We study distributed optimization where nodes co-operatively minimize the sum of their indi...
Abstract We propose a novel distributed method for convex optimization problems with a certain separ...
A multi-agent optimization problem motivated by the management of energy systems is discussed. The a...
Abstract — In this paper, we propose a distributed algorithm for optimal routing in wireless multi-h...
Ce talk est un des trois "exposés phares" invités par Olivier BeaumontNational audienceLarge scale d...
International audienceIn this article, we illustrate practical issues arising in the development of ...
A multi-agent optimization problem motivated by the management of energy systems is discussed. The a...
We study the convergence speed of distributed iterative algorithms for the consensus and averaging p...
We propose three new algorithms for the distributed averaging and consensus prob-lems: two for the f...
In this paper, we compare six known linear distributed average consensus algorithms on a sensor netw...
This paper presents an empirical study of the convergence characteristics of augmented Lagrangian co...
Abstract — Consider a set of N agents seeking to solve dis-tributively the minimization problem infx...
We study distributed optimization in networked systems, where nodes cooperate to find the optimal qu...
This paper gives a lower bound on the convergence rate of a class of network consensus algorithms. T...