Dissimilarity in Graph-Based Semi-Supervised Classification

  title={Dissimilarity in Graph-Based Semi-Supervised Classification},
  author={Andrew B. Goldberg and Xiaojin Zhu and Stephen J. Wright},
Label dissimilarity specifies that a pair of examples probably have different class labels. We present a semi-supervised classification algorithm that learns from dissimilarity and similarity information on labeled and unlabeled data. Our approach uses a novel graphbased encoding of dissimilarity that results in a convex problem, and can handle both binary and multiclass classification. Experiments on several tasks are promising. 
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Mooney . Probabilistic semi - supervised clustering with constraints

  • Olivier Chapelle, Alexander Zien, Bernhard Schölkopf
  • Manifold regularization : A geometric framework…
  • 2006

Semisupervised regression with order preferences

  • Xiaojin Zhu, Andrew B. Goldberg
  • Technical Report TR1578,
  • 2006
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