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.
Categories: cs.DS