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New Notions and Constructions of Sparsification for Graphs and Hypergraphs

Abstract

A sparsifier of a graph GG (Bencz\'ur and Karger; Spielman and Teng) is a sparse weighted subgraph G~\tilde G that approximately retains the cut structure of GG. For general graphs, non-trivial sparsification is possible only by using weighted graphs in which different edges have different weights. Even for graphs that admit unweighted sparsifiers, there are no known polynomial time algorithms that find such unweighted sparsifiers. We study a weaker notion of sparsification suggested by Oveis Gharan, in which the number of edges in each cut (S,Sˉ)(S,\bar S) is not approximated within a multiplicative factor (1+ϵ)(1+\epsilon), but is, instead, approximated up to an additive term bounded by ϵ\epsilon times dS+vol(S)d\cdot |S| + \text{vol}(S), where dd is the average degree, and vol(S)\text{vol}(S) is the sum of the degrees of the vertices in SS. We provide a probabilistic polynomial time construction of such sparsifiers for every graph, and our sparsifiers have a near-optimal number of edges O(ϵ2npolylog(1/ϵ))O(\epsilon^{-2} n {\rm polylog}(1/\epsilon)). We also provide a deterministic polynomial time construction that constructs sparsifiers with a weaker property having the optimal number of edges O(ϵ2n)O(\epsilon^{-2} n). Our constructions also satisfy a spectral version of the ``additive sparsification'' property. Our construction of ``additive sparsifiers'' with Oϵ(n)O_\epsilon (n) edges also works for hypergraphs, and provides the first non-trivial notion of sparsification for hypergraphs achievable with O(n)O(n) hyperedges when ϵ\epsilon and the rank rr of the hyperedges are constant. Finally, we provide a new construction of spectral hypergraph sparsifiers, according to the standard definition, with poly(ϵ1,r)nlogn{\rm poly}(\epsilon^{-1},r)\cdot n\log n hyperedges, improving over the previous spectral construction (Soma and Yoshida) that used O~(n3)\tilde O(n^3) hyperedges even for constant rr and ϵ\epsilon.Comment: 31 page

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