@InProceedings{CI-boria-2019,


author = {Nicolas Boria and Sébastien Bougleux and Benoit Gaüzère and Luc Brun},
title = {Generalized Median Graph via Iterative Alternate Minimizations},
booktitle = {Proceedings of the International 12th workshop on Graph-Based Representation in Pattern Recognition},
year = 2019,
editor = {Donatello Conte and Jean-Yves Ramel},
series = {LNCS},
month = {June},
address = {Tours},
organization = {IAPR},
publisher = {Springer},
url={HAL:=https://hal-normandie-univ.archives-ouvertes.fr/hal-02162838},
theme="pattern",
abstract="Computing a graph prototype may constitute a core element
for clustering or classification tasks. However, its computation is an NP-
Hard problem, even for simple classes of graphs. In this paper, we propose
an efficient approach based on block coordinate descent to compute a
generalized median graph from a set of graphs. This approach relies on a
clear definition of the optimization process and handles labeling on both
edges and nodes. This iterative process optimizes the edit operations to
perform on a graph alternatively on nodes and edges. Several experiments
on different datasets show the efficiency of our approach."

 }