• Corpus ID: 88513124

Seeded Graph Matching Via Joint Optimization of Fidelity and Commensurability.

@article{Patsolic2014SeededGM,
  title={Seeded Graph Matching Via Joint Optimization of Fidelity and Commensurability.},
  author={Heather G. Patsolic and Sancar Adali and Joshua T. Vogelstein and Youngser Park and Carey E. Friebe and Gongkai Li and Vince Lyzinski},
  journal={arXiv: Machine Learning},
  year={2014}
}
We present a novel approximate graph matching algorithm that incorporates seeded data into the graph matching paradigm. Our Joint Optimization of Fidelity and Commensurability (JOFC) algorithm embeds two graphs into a common Euclidean space where the matching inference task can be performed. Through real and simulated data examples, we demonstrate the versatility of our algorithm in matching graphs with various characteristics--weightedness, directedness, loopiness, many-to-one and many-to-many… 

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