Distributed Algorithms for SCC Decomposition

Distributed Algorithms for SCC Decomposition

We study existing parallel algorithms for the decomposition of a partitioned graph into its strongly connected components. In particular, we identify several individual procedures that the algorithms are assembled from and show how to assemble a new and more efficient algorithm, called Recursive OBF, to solve the decomposition problem. We also report on a thorough experimental study to evaluate...

Biconjugate Decomposition Using ABS Algorithms

Decomposition Algorithms for Distributionally

We study distributionally robust optimization (DRO) problems where the ambiguity 4 set is defined using the Wasserstein metric. We show that this class of DRO problems can be 5 reformulated as semi-infinite programs. We give an exchange method to solve the reformulated 6 problem for the general nonlinear model, and a central cutting-surface method for the convex case, 7 assuming that we have a ...

Parallel and distributed vision algorithms using dual decomposition

We investigate dual decomposition approaches for optimization problems arising in low-level vision. Dual decomposition can be used to parallelize existing algorithms, reduce memory requirements and to obtain approximate solutions of hard problems. An extensive set of experiments are performed for a variety of application problems including graph cut segmentation, curvature regularization and mo...

Refining SCC decomposition in argumentation semantics: a first investigation

In the recently proposed SCC-recursive approach to argumentation semantics, the strongly connected components of an argumentation framework are used as the basic elements for the incremental construction of extensions. In this paper we argue that a finer decomposition, considering some suitably defined internal substructures of strongly connected components, called autonomous fragments, may be ...