Department of Mathematics
 Search | Help | Login | pdf version | printable version

Math @ Duke



Publications [#264717] of Guillermo Sapiro

Papers Published

  1. Fiori, M; Sprechmann, P; Vogelstein, J; Musé, P; Sapiro, G, Robust multimodal graph matching: Sparse coding meets graph matching, Advances in Neural Information Processing Systems (January, 2013), ISSN 1049-5258
    (last updated on 2017/12/14)

    Graph matching is a challenging problem with very important applications in a wide range of fields, from image and video analysis to biological and biomedical problems. We propose a robust graph matching algorithm inspired in sparsity-related techniques. We cast the problem, resembling group or collaborative sparsity formulations, as a non-smooth convex optimization problem that can be efficiently solved using augmented Lagrangian techniques. The method can deal with weighted or unweighted graphs, as well as multimodal data, where different graphs represent different types of data. The proposed approach is also naturally integrated with collaborative graph inference techniques, solving general network inference problems where the observed variables, possibly coming from different modalities, are not in correspondence. The algorithm is tested and compared with state-of-the-art graph matching techniques in both synthetic and real graphs. We also present results on multimodal graphs and applications to collaborative inference of brain connectivity from alignment-free functional magnetic resonance imaging (fMRI) data. The code is publicly available.
ph: 919.660.2800
fax: 919.660.2821

Mathematics Department
Duke University, Box 90320
Durham, NC 27708-0320