Partitioning sparse matrices with eigenvectors of graphs
SIAM Journal on Matrix Analysis and Applications
Singular value decomposition: an introduction
SVD and signal processing
Separators for sphere-packings and nearest neighbor graphs
Journal of the ACM (JACM)
Combinatorial aspects of geometric graphs
Computational Geometry: Theory and Applications
Complexity of graph partition problems
STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
Shallow excluded minors and improved graph decompositions
SODA '94 Proceedings of the fifth annual ACM-SIAM symposium on Discrete algorithms
Finding nearest neighbors in growth-restricted metrics
STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
Spectral partitioning works: planar graphs and finite element meshes
FOCS '96 Proceedings of the 37th Annual Symposium on Foundations of Computer Science
STOC '04 Proceedings of the thirty-sixth annual ACM symposium on Theory of computing
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Miller, Teng, Thurston, and Vavasis proved that every k- nearest neighbor graph (k-NNG) in Rdhas a balanced vertex separator of size O(n1-1/dk1/d). Later, Spielman and Teng proved that the Fiedler value -- the second smallest eigenvalue of the graph -- of the Laplacian matrix of a k-NNG in Rd is at O(1/n2/d). In this paper, we extend these two results to nearest neighbor graphs in a metric space with doubling dimension γ and in nearly-Euclidean spaces. We prove that for every l 0, each k-NNG in a metric space with doubling dimension γ has a vertex separator of size O(k2l(32l + 8)2γ log2 L/S log n + n/l), where L and S are respectively the maximum and minimum distances between any two points in P, and P is the point set that constitutes the metric space. We show how to use the singular value decomposition method to approximate a k-NNG in a nearly-Euclidean space by an Euclidean k-NNG. This approximation enables us to obtain an upper bound on the Fiedler value of the k-NNG in a nearly-Euclidean space.