Spectral Clustering and Block Models: A Review And A New Algorithm
Statistics Theory
2015-08-11 v1 Social and Information Networks
Machine Learning
Statistics Theory
Abstract
We focus on spectral clustering of unlabeled graphs and review some results on clustering methods which achieve weak or strong consistent identification in data generated by such models. We also present a new algorithm which appears to perform optimally both theoretically using asymptotic theory and empirically.
Keywords
Cite
@article{arxiv.1508.01819,
title = {Spectral Clustering and Block Models: A Review And A New Algorithm},
author = {Sharmodeep Bhattacharyya and Peter J. Bickel},
journal= {arXiv preprint arXiv:1508.01819},
year = {2015}
}
Comments
27 pages