Higher-Order Cheeger Inequality for Partitioning with Buffers

08/20/2023
by   Konstantin Makarychev, et al.
0

We prove a new generalization of the higher-order Cheeger inequality for partitioning with buffers. Consider a graph G=(V,E). The buffered expansion of a set S ⊆ V with a buffer B ⊆ V ∖ S is the edge expansion of S after removing all the edges from set S to its buffer B. An ε-buffered k-partitioning is a partitioning of a graph into disjoint components P_i and buffers B_i, in which the size of buffer B_i for P_i is small relative to the size of P_i: |B_i| ≤ε |P_i|. The buffered expansion of a buffered partition is the maximum of buffered expansions of the k sets P_i with buffers B_i. Let h^k,ε_G be the buffered expansion of the optimal ε-buffered k-partitioning, then for every δ>0, h_G^k,ε≤ O_δ(1) ·( log k/ε) ·λ_⌊ (1+δ) k⌋, where λ_⌊ (1+δ)k⌋ is the ⌊ (1+δ)k⌋-th smallest eigenvalue of the normalized Laplacian of G. Our inequality is constructive and avoids the “square-root loss” that is present in the standard Cheeger inequalities (even for k=2). We also provide a complementary lower bound, and a novel generalization to the setting with arbitrary vertex weights and edge costs. Moreover our result implies and generalizes the standard higher-order Cheeger inequalities and another recent Cheeger-type inequality by Kwok, Lau, and Lee (2017) involving robust vertex expansion.

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