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arXiv · 1906.11009

Generalized Median Graph via Iterative Alternate Minimizations

Nicolas Boria·S'ebastien Bougleux·Benoit Gaüzère·Luc Brun
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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.

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Nicolas Boria, S'ebastien Bougleux, Benoit Gaüzère, Luc Brun. 2019-06-26. Generalized Median Graph via Iterative Alternate Minimizations. https://arxiv.org/abs/1906.11009

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