ADD-OPT swMATH ID: 25783 Software Authors: Xi, Chenguang; Xin, Ran; Khan, Usman A. Description: ADD-OPT: accelerated distributed directed optimization. In this paper, we consider distributed optimization problems where the goal is to minimize a sum of objective functions over a multi-agent network. We focus on the case when the inter-agent communication is described by a strongly-connected, emph{directed} graph. The proposed algorithm, ADD-OPT (Accelerated Distributed Directed Optimization), achieves the best known convergence rate for this class of problems, O(μk),0<μ<1, given strongly-convex, objective functions with globally Lipschitz-continuous gradients, where k is the number of iterations. Moreover, ADD-OPT supports a wider and more realistic range of step-sizes in contrast to existing work. In particular, we show that ADD-OPT converges for arbitrarily small (positive) step-sizes. Simulations further illustrate our results. Homepage: http://www.google.de/#sclient=psy&hl=de&source=hp&q=ADD-OPT Related Software: HOGWILD; AIDE Cited in: 3 Publications Standard Articles 1 Publication describing the Software, including 1 Publication in zbMATH Year ADD-OPT: accelerated distributed directed optimization. Zbl 1395.90204Xi, Chenguang; Xin, Ran; Khan, Usman A. 2018 all top 5 Cited by 10 Authors 1 Cen, Shicong 1 Chen, Yuxin 1 Chi, Yuejie 1 Khan, Usman Ali 1 Li, Boyue 1 Olshevsky, Alex 1 Paschalidis, Ioannis Ch. 1 Spiridonoff, Artin 1 Xi, Chenguang 1 Xin, Ran Cited in 2 Serials 2 Journal of Machine Learning Research (JMLR) 1 IEEE Transactions on Automatic Control Cited in 2 Fields 2 Operations research, mathematical programming (90-XX) 1 Computer science (68-XX) Citations by Year