Suppose we are given a graph G = (V, E) and a set of terminals K ⊂ V. We consider the problem of constructing a graph H = (K, E[subscript H]) that approximately preserves the congestion of every multicommodity flow with endpoints supported in K. We refer to such a graph as a flow sparsifier. We prove that there exist flow sparsifiers that simultaneously preserve the congestion of all multicommodity flows within an O(log k / log log k)-factor where |K| = k. This bound improves to O(1) if G excludes any fixed minor. This is a strengthening of previous results, which consider the problem of finding a graph H = (K, E[subscript H]) (a cut sparsifier) that approximately preserves the value of minimum cuts separating any partition of the terminals...
A cut [S.S] is a sparsest cut of a graph G if its cut value [S][S]/[S.S] is maximum (this is the rec...
AbstractA cut [S,S̄] is a sparsest cut of a graph G if its cut value |S||S̄|/|[S,S̄]| is maximum (th...
In this paper we present two combinatorial algorithms for Sparsest Cut which achieve an O(logn) appr...
Abstract. Given a capacitated graph G = (V, E) and a set of terminals K ⊆ V, how should we produce a...
Given a capacitated graph G = (V,E) and a set of terminals K ⊆ V, how should we produce a graph H on...
Given a capacitated graph G = (V, E) and a set of terminals K subset of V, how should we produce a g...
Graph Sparsification aims at compressing large graphs into smaller ones while (approximately) preser...
Given an undirected graph G = (V,E) with edge capacities ce ≥ 1 for e ∈ E and a subset T of k vertic...
Given a capacitated graph G = (V, E) and a set of terminals K ⊆ V, how should we produce a graph H o...
Linial, London and Rabinovich [16] and Aumann and Rabani [3] proved that the min-cut max-flow ratio ...
The notion of vertex sparsification (in particular cut-sparsification) is introduced in, where it wa...
A useful approach to “compress” a large network G is to represent it with a flow-sparsifier, i.e., a...
A useful approach to “compress ” a large network G is to represent it with a flow-sparsifier, i.e., ...
Graph Sparsification aims at compressing large graphs into smaller ones while (approximately) preser...
Abstract. In this paper, we introduce a new framework for approximately solving flow problems in cap...
A cut [S.S] is a sparsest cut of a graph G if its cut value [S][S]/[S.S] is maximum (this is the rec...
AbstractA cut [S,S̄] is a sparsest cut of a graph G if its cut value |S||S̄|/|[S,S̄]| is maximum (th...
In this paper we present two combinatorial algorithms for Sparsest Cut which achieve an O(logn) appr...
Abstract. Given a capacitated graph G = (V, E) and a set of terminals K ⊆ V, how should we produce a...
Given a capacitated graph G = (V,E) and a set of terminals K ⊆ V, how should we produce a graph H on...
Given a capacitated graph G = (V, E) and a set of terminals K subset of V, how should we produce a g...
Graph Sparsification aims at compressing large graphs into smaller ones while (approximately) preser...
Given an undirected graph G = (V,E) with edge capacities ce ≥ 1 for e ∈ E and a subset T of k vertic...
Given a capacitated graph G = (V, E) and a set of terminals K ⊆ V, how should we produce a graph H o...
Linial, London and Rabinovich [16] and Aumann and Rabani [3] proved that the min-cut max-flow ratio ...
The notion of vertex sparsification (in particular cut-sparsification) is introduced in, where it wa...
A useful approach to “compress” a large network G is to represent it with a flow-sparsifier, i.e., a...
A useful approach to “compress ” a large network G is to represent it with a flow-sparsifier, i.e., ...
Graph Sparsification aims at compressing large graphs into smaller ones while (approximately) preser...
Abstract. In this paper, we introduce a new framework for approximately solving flow problems in cap...
A cut [S.S] is a sparsest cut of a graph G if its cut value [S][S]/[S.S] is maximum (this is the rec...
AbstractA cut [S,S̄] is a sparsest cut of a graph G if its cut value |S||S̄|/|[S,S̄]| is maximum (th...
In this paper we present two combinatorial algorithms for Sparsest Cut which achieve an O(logn) appr...