Unified Statistical Theory of Spectral Graph Analysis
arXiv:1602.03861
Abstract
The goal of this paper is to show that there exists a simple, yet universal statistical logic of spectral graph analysis by recasting it into a nonparametric function estimation problem. The prescribed viewpoint appears to be good enough to accommodate most of the existing spectral graph techniques as a consequence of just one single formalism and algorithm.
Major changes have been done in terms of contents and structure of the paper. New set of motivations for GraField, Expanding Section 4, Connections with Diffusion map and Google's PageRank method etc
References in corpus (5)
- Finding community structure in networks using the eigenvectors of matrices
- Consistency of spectral clustering
- Stochastic blockmodel approximation of a graphon: Theory and consistent estimation
- Spectral methods for the detection of network community structure: a comparative analysis
- Strength of Connections in a Random Graph: Definition, Characterization, and Estimation