Higher-Order Cheeger Inequality for Partitioning with Buffers

August 20, 2023 Β· Declared Dead Β· πŸ› ACM-SIAM Symposium on Discrete Algorithms

πŸ‘» CAUSE OF DEATH: Ghosted
No code link whatsoever

"No code URL or promise found in abstract"

Evidence collected by the PWNC Scanner

Authors Konstantin Makarychev, Yury Makarychev, Liren Shan, Aravindan Vijayaraghavan arXiv ID 2308.10160 Category cs.DS: Data Structures & Algorithms Citations 1 Venue ACM-SIAM Symposium on Discrete Algorithms Last Checked 4 months ago
Abstract
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 $S \subseteq V$ with a buffer $B \subseteq V \setminus S$ is the edge expansion of $S$ after removing all the edges from set $S$ to its buffer $B$. An $\varepsilon$-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 $P_i$: $|B_i| \le \varepsilon |P_i|$. The buffered expansion of a buffered partition is the maximum of buffered expansions of the $k$ sets $P_i$ with buffers $B_i$. Let $h^{k,\varepsilon}_G$ be the buffered expansion of the optimal $\varepsilon$-buffered $k$-partitioning, then for every $Ξ΄>0$, $$h_G^{k,\varepsilon} \le O_Ξ΄(1) \cdot \Big( \frac{\log k}{ \varepsilon}\Big) \cdot Ξ»_{\lfloor (1+Ξ΄) k\rfloor},$$ where $Ξ»_{\lfloor (1+Ξ΄)k\rfloor}$ is the $\lfloor (1+Ξ΄)k\rfloor$-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.
Community shame:
Not yet rated
Community Contributions

Found the code? Know the venue? Think something is wrong? Let us know!

πŸ“œ Similar Papers

In the same crypt β€” Data Structures & Algorithms

Died the same way β€” πŸ‘» Ghosted