A Consistent Histogram Estimator for Exchangeable Graph Models
Methodology
2014-02-12 v2
Abstract
Exchangeable graph models (ExGM) subsume a number of popular network models. The mathematical object that characterizes an ExGM is termed a graphon. Finding scalable estimators of graphons, provably consistent, remains an open issue. In this paper, we propose a histogram estimator of a graphon that is provably consistent and numerically efficient. The proposed estimator is based on a sorting-and-smoothing (SAS) algorithm, which first sorts the empirical degree of a graph, then smooths the sorted graph using total variation minimization. The consistency of the SAS algorithm is proved by leveraging sparsity concepts from compressed sensing.
Cite
@article{arxiv.1402.1888,
title = {A Consistent Histogram Estimator for Exchangeable Graph Models},
author = {Stanley H. Chan and Edoardo M. Airoldi},
journal= {arXiv preprint arXiv:1402.1888},
year = {2014}
}
Comments
28 pages, 5 figures