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Publications [#322686] of Guillermo Sapiro

Papers Published

  1. Huang, J; Qiu, Q; Calderbank, R; Rodrigues, M; Sapiro, G, Alignment with intra-class structure can improve classification, 2015 Ieee International Conference on Acoustics, Speech, and Signal Processing (Icassp), vol. 2015-August (January, 2015), pp. 1921-1925, IEEE, ISBN 9781467369978 [doi]
    (last updated on 2019/06/17)

    © 2015 IEEE. High dimensional data is modeled using low-rank subspaces, and the probability of misclassification is expressed in terms of the principal angles between subspaces. The form taken by this expression motivates the design of a new feature extraction method that enlarges inter-class separation, while preserving intra-class structure. The method can be tuned to emphasize different features shared by members within the same class. Classification performance is compared to that of state-of-the-art methods on synthetic data and on the real face database. The probability of misclassification is decreased when intra-class structure is taken into account.
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Mathematics Department
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