NeurIPS 2020poster24 citations
On the Power of Louvain in the Stochastic Block Model
Vincent Cohen-Addad, Adrian Kosowski, Frederik Mallmann-Trenn, David Saulpic
Abstract
A classic problem in machine learning and data analysis is to partition the vertices of a network in such a way that vertices in the same set are densely connected and vertices in different sets are loosely connected.
BibTeX
@inproceedings{NEURIPS2020_29a6aa8a,
author = {Cohen-Addad, Vincent and Kosowski, Adrian and Mallmann-Trenn, Frederik and Saulpic, David},
booktitle = {Advances in Neural Information Processing Systems},
editor = {H. Larochelle and M. Ranzato and R. Hadsell and M.F. Balcan and H. Lin},
pages = {4055--4066},
publisher = {Curran Associates, Inc.},
title = {On the Power of Louvain in the Stochastic Block Model},
url = {https://proceedings.neurips.cc/paper_files/paper/2020/file/29a6aa8af3c942a277478a90aa4cae21-Paper.pdf},
volume = {33},
year = {2020}
}