Dissimilarity in Graph-Based Semi-Supervised Classification

@inproceedings{Goldberg2007DissimilarityIG,
  title={Dissimilarity in Graph-Based Semi-Supervised Classification},
  author={Andrew B. Goldberg and Xiaojin Zhu and Stephen J. Wright},
  booktitle={AISTATS},
  year={2007}
}
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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