Preprocessing Graphs for Network Inference Applications

H. R. Sachin Prabhu, Hua-Liang Wei

2017

Abstract

The problem of network inference can be solved as a constrained matrix factorization problem where some sparsity constraints are imposed on one of the matrix factors. The solution is unique up to a scaling factor when certain rank conditions are imposed on both the matrix factors. Two key issues in factorising a matrix of data from some netwrok are that of establishing simple identifiability conditions and decomposing a network into identifiable subnetworks. This paper solves both the problems by introducing the notion of an ordered matching in a bipartite graphs. Novel and simple graph theoretical conditions are developed which can replace the aforementioned computationally intensive rank conditions. A simple algorithm to reduce a bipartite graph and a graph preprocessing algorithm to decompose a network into a set of identifiable subsystems is proposed.

Paper Citation

in Harvard Style

Prabhu H. and Wei H. (2017). Preprocessing Graphs for Network Inference Applications . In Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-263-9, pages 406-413. DOI: 10.5220/0006401104060413

in Bibtex Style

@conference{icinco17,
author={H. R. Sachin Prabhu and Hua-Liang Wei},
title={Preprocessing Graphs for Network Inference Applications},
booktitle={Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2017},
pages={406-413},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006401104060413},
isbn={978-989-758-263-9},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Preprocessing Graphs for Network Inference Applications
SN - 978-989-758-263-9
AU - Prabhu H.
AU - Wei H.
PY - 2017
SP - 406
EP - 413
DO - 10.5220/0006401104060413