Manifold-based Similarity Adaptation for Label Propagation

  title={Manifold-based Similarity Adaptation for Label Propagation},
  author={Masayuki Karasuyama and Hiroshi Mamitsuka},
Label propagation is one of the state-of-the-art methods for semi-supervised learning, which estimates labels by propagating label information through a graph. Label propagation assumes that data points (nodes) connected in a graph should have similar labels. Consequently, the label estimation heavily depends on edge weights in a graph which represent similarity of each node pair. We propose a method for a graph to capture the manifold structure of input features using edge weights… CONTINUE READING
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