10,551 research outputs found

    Near-optimum universal graphs for graphs with bounded degrees (Extended abstract)

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    Let H be a family of graphs. We say that G is H-universal if, for each H ∈H, the graph G contains a subgraph isomorphic to H. Let H(k, n) denote the family of graphs on n vertices with maximum degree at most k. For each fixed k and each n sufficiently large, we explicitly construct an H(k, n)-universal graph Γ(k, n) with O(n2−2/k(log n)1+8/k) edges. This is optimal up to a small polylogarithmic factor, as Ω(n2−2/k) is a lower bound for the number of edges in any such graph. En route, we use the probabilistic method in a rather unusual way. After presenting a deterministic construction of the graph Γ(k, n), we prove, using a probabilistic argument, that Γ(k, n) is H(k, n)-universal. So we use the probabilistic method to prove that an explicit construction satisfies certain properties, rather than showing the existence of a construction that satisfies these properties. © Springer-Verlag Berlin Heidelberg 200

    Towards a better approximation for sparsest cut?

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    We give a new (1+ϵ)(1+\epsilon)-approximation for sparsest cut problem on graphs where small sets expand significantly more than the sparsest cut (sets of size n/rn/r expand by a factor lognlogr\sqrt{\log n\log r} bigger, for some small rr; this condition holds for many natural graph families). We give two different algorithms. One involves Guruswami-Sinop rounding on the level-rr Lasserre relaxation. The other is combinatorial and involves a new notion called {\em Small Set Expander Flows} (inspired by the {\em expander flows} of ARV) which we show exists in the input graph. Both algorithms run in time 2O(r)poly(n)2^{O(r)} \mathrm{poly}(n). We also show similar approximation algorithms in graphs with genus gg with an analogous local expansion condition. This is the first algorithm we know of that achieves (1+ϵ)(1+\epsilon)-approximation on such general family of graphs

    Reducing Maximum Stretch in Compact Routing

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