Approximating the exponential, the lanczos method and an Õ(m)-time spectral algorithm for balanced separator

  • Authors:

  • Lorenzo Orecchia;Sushant Sachdeva;Nisheeth K. Vishnoi

  • Affiliations:

  • Massachusetts Institute of Technology, Cambridge, MA, USA;Princeton University, Princeton, NJ, USA;Microsoft Research, Bangalore, India

  • Venue:
  • STOC '12 Proceedings of the forty-fourth annual ACM symposium on Theory of computing
  • Year:
  • 2012

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Abstract

We give a novel spectral approximation algorithm for the balanced (edge-)separator problem that, given a graph G, a constant balance b ∈ (0,1/2], and a parameter γ, either finds an Ω(b)-balanced cut of conductance O(√γ) in G, or outputs a certificate that all b-balanced cuts in G have conductance at least γ, and runs in time ~O(m). This settles the question of designing asymptotically optimal spectral algorithms for balanced separator. Our algorithm relies on a variant of the heat kernel random walk and requires, as a subroutine, an algorithm to compute exp(-L)v where L is the Laplacian of a graph related to G and v is a vector. Algorithms for computing the matrix-exponential-vector product efficiently comprise our next set of results. Our main result here is a new algorithm which computes a good approximation to exp(-A)v for a class of symmetric positive semidefinite (PSD) matrices A and a given vector v, in time roughly ~O(mA), independent of the norm of A, where mA is the number of non-zero entries of A. This uses, in a non-trivial way, the result of Spielman and Teng on inverting symmetric and diagonally-dominant matrices in ~O(mA) time. Finally, using old and new uniform approximations to e-x we show how to obtain, via the Lanczos method, a simple algorithm to compute exp(-A)v for symmetric PSD matrices that runs in time roughly O(tA⋅ √norm(A)), where tA is the time required for the computation of the vector Aw for given vector w. As an application, we obtain a simple and practical algorithm, with output conductance O(√γ), for balanced separator that runs in time O(m/√γ). This latter algorithm matches the running time, but improves on the approximation guarantee of the Evolving-Sets-based algorithm by Andersen and Peres for balanced separator.