11 research outputs found
Improved guarantees for Vertex Sparsification in planar graphs
Graph Sparsification aims at compressing large graphs into smaller ones while (approximately) preserving important characteristics of the input graph. In this work we study Vertex Sparsifiers, i.e., sparsifiers whose goal is to reduce the number of vertices. Given a weighted graph G=(V,E), and a terminal set K with |K|=k, a quality-q vertex cut sparsifier of G is a graph H with K contained in V_H that preserves the value of minimum cuts separating any bipartition of K, up to a factor of q. We show that planar graphs with all the k terminals lying on the same face admit quality-1 vertex cut sparsifier of size O(k^2) that are also planar. Our result extends to vertex flow and distance sparsifiers. It improves the previous best known bound of O(k^2 2^(2k)) for cut and flow sparsifiers by an exponential factor, and matches an Omega(k^2) lower-bound for this class of graphs. We also study vertex reachability sparsifiers for directed graphs. Given a digraph G=(V,E) and a terminal set K, a vertex reachability sparsifier of G is a digraph H=(V_H,E_H), K contained in V_H that preserves all reachability information among terminal pairs. We introduce the notion of reachability-preserving minors, i.e., we require H to be a minor of G. Among others, for general planar digraphs, we construct reachability-preserving minors of size O(k^2 log^2 k). We complement our upper-bound by showing that there exists an infinite family of acyclic planar digraphs such that any reachability-preserving minor must have Omega(k^2) vertices
Steiner Point Removal with Distortion
In the Steiner point removal (SPR) problem, we are given a weighted graph
and a set of terminals of size . The objective is to
find a minor of with only the terminals as its vertex set, such that
the distance between the terminals will be preserved up to a small
multiplicative distortion. Kamma, Krauthgamer and Nguyen [KKN15] used a
ball-growing algorithm with exponential distributions to show that the
distortion is at most . Cheung [Che17] improved the analysis of
the same algorithm, bounding the distortion by . We improve the
analysis of this ball-growing algorithm even further, bounding the distortion
by
A regularization perspective on spectral sparsification
In this thesis, we study how to obtain faster algorithms for spectral graph sparsifi-cation by applying continuous optimization techniques. Spectral sparsification is thetask of reducing the number of edges in a graph while maintaining a spectral ap-proximation to the original graph. Our key conceptual contribution is the connectionbetween spectral sparsification and regret minimization in online matrix games, i.e.,online convex programming over the positive semidefinite cone. While this connec-tion was previously noted [24, 47], we formally reduce graph sparsification to a matrixregret minimization problem, which we solve by applying mirror descent with a non-entropic regularizer. In this way, we not only obtain a new proof of the existenceof linear-sized spectral sparsifiers, originally given by [19], but improve the runningtime from Ω(n4)([19, 54]) to almost quadratic. More generally, our framework canalso be applied for the matrix multi-armed bandit online learning problem to reducethe regret bound to the optimalO(√nT), compared to theO(√nTlog(n) given bythe traditional matrix-entropy regulari
Network Sparsification for Steiner Problems on Planar and Bounded-Genus Graphs
We propose polynomial-time algorithms that sparsify planar and bounded-genus
graphs while preserving optimal or near-optimal solutions to Steiner problems.
Our main contribution is a polynomial-time algorithm that, given an unweighted
graph embedded on a surface of genus and a designated face bounded
by a simple cycle of length , uncovers a set of size
polynomial in and that contains an optimal Steiner tree for any set of
terminals that is a subset of the vertices of .
We apply this general theorem to prove that: * given an unweighted graph
embedded on a surface of genus and a terminal set , one
can in polynomial time find a set that contains an optimal
Steiner tree for and that has size polynomial in and ; * an
analogous result holds for an optimal Steiner forest for a set of terminal
pairs; * given an unweighted planar graph and a terminal set , one can in polynomial time find a set that contains
an optimal (edge) multiway cut separating and that has size polynomial
in .
In the language of parameterized complexity, these results imply the first
polynomial kernels for Steiner Tree and Steiner Forest on planar and
bounded-genus graphs (parameterized by the size of the tree and forest,
respectively) and for (Edge) Multiway Cut on planar graphs (parameterized by
the size of the cutset). Additionally, we obtain a weighted variant of our main
contribution