RC Circuits based Distributed Conditional Gradient Method

We consider distributed optimization on undirected connected graphs. We propose a novel distributed conditional gradient method with (O(1/\sqrt{k})) convergence. Compared with existing methods, each iteration of our method uses both communication and linear minimization step only once rather than multiple times. We further extend our results to cases with composite local constraints. We demonstrate our results via examples on distributed matrix completion problem.