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Guruswami-Sinop Rounding without Higher Level Lasserre (1406.7279v1)

Published 27 Jun 2014 in cs.DS

Abstract: Guruswami and Sinop give a $O(1/\delta)$ approximation guarantee for the non-uniform Sparsest Cut problem by solving $O(r)$-level Lasserre semidefinite constraints, provided that the generalized eigenvalues of the Laplacians of the cost and demand graphs satisfy a certain spectral condition, namely, $\lambda_{r+1} \geq \Phi{*}/(1-\delta)$. Their key idea is a rounding technique that first maps a vector-valued solution to $[0, 1]$ using appropriately scaled projections onto Lasserre vectors. In this paper, we show that similar projections and analysis can be obtained using only $\ell_{2}{2}$ triangle inequality constraints. This results in a $O(r/\delta{2})$ approximation guarantee for the non-uniform Sparsest Cut problem by adding only $\ell_{2}{2}$ triangle inequality constraints to the usual semidefinite program, provided that the same spectral condition, $\lambda_{r+1} \geq \Phi{*}/(1-\delta)$, holds.

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