Abstract:In this paper, we propose GT-GDA, a distributed optimization method to solve saddle point problems of the form: minx maxy F (x, y) := G(x) + y, P x − H(y) , where the functions G(•), H(•), and the the coupling matrix P are distributed over a strongly connected network of nodes. GT-GDA is a first-order method that uses gradient tracking to eliminate the dissimilarity caused by heterogeneous data distribution among the nodes. In the most general form, GT-GDA includes a consensus over the local coupling matrices … Show more
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