Improved ARV Rounding in Small-set Expanders and Graphs of Bounded Threshold Rank

We prove a structure theorem for the feasible solutions of the Arora-Rao-Vazirani SDP relaxation on low threshold rank graphs and on small-set expanders. We show that if G is a graph of bounded threshold rank or a small-set expander, then an optimal solution of the Arora-Rao-Vazirani relaxation (or of any stronger version of it) can be almost entirely covered by a small number of balls of bounded radius. Then, we show that, if k is the number of balls, a solution of this form can be rounded with an approximation factor of O(sqrt {log k}) in the case of the Arora-Rao-Vazirani relaxation, and with a constant-factor approximation in the case of the k-th round of the Sherali-Adams hierarchy starting at the Arora-Rao-Vazirani relaxation. The structure theorem and the rounding scheme combine to prove the following result, where G=(V,E) is a graph of expansion \phi(G), \lambdak is the k-th smallest eigenvalue of the normalized Laplacian of G, and \phik(G) = \min{disjoint S1,...,Sk} \max{1 <= i <= k} \phi(Si) is the largest expansion of any k disjoint subsets of V: if either \lambdak >> log^{2.5} k \cdot phi(G) or \phi{k} (G) >> log k \cdot sqrt{log n}\cdot loglog n\cdot \phi(G), then the Arora-Rao-Vazirani relaxation can be rounded in polynomial time with an approximation ratio O(sqrt{log k}). Stronger approximation guarantees are achievable in time exponential in k via relaxations in the Lasserre hierarchy. Guruswami and Sinop [GS13] and Arora, Ge and Sinop [AGS13] prove that 1+eps approximation is achievable in time 2^{O(k)} poly(n) if either \lambdak > \phi(G)/ poly(eps), or if SSE{n/k} > sqrt{log k log n} \cdot \phi(G)/ poly(eps), where SSEs is the minimal expansion of sets of size at most s.