@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."
}