Motivated by the fact that entities in a social network or biological system often interact by exchanging information, we propose an efficient info-clustering algorithm that can group entities into communities using a parametric max-flow algorithm. This is a meaningful special case of the info-clustering paradigm where the dependency structure is graphical and can be learned readily from data.
@article{arxiv.1702.00109,
title = {Info-Clustering: An Efficient Algorithm by Network Information Flow},
author = {Chung Chan and Ali Al-Bashabsheh and Qiaoqiao Zhou},
journal= {arXiv preprint arXiv:1702.00109},
year = {2017}
}