Convergence Rate of the Symmetrically Normalized Graph Laplacian
Differential Geometry
2011-01-10 v1
Abstract
This short note aims at (re)proving that the symmetrically normalized graph Laplacian (from a graph defined from a Gaussian weighting kernel on a sampled smooth manifold) converges towards the continuous Manifold Laplacian when the sampling become infinitely dense. The convergence rate with respect to the number of samples is .
Keywords
Cite
@article{arxiv.1101.1428,
title = {Convergence Rate of the Symmetrically Normalized Graph Laplacian},
author = {Laurent Jacques},
journal= {arXiv preprint arXiv:1101.1428},
year = {2011}
}