Beyond pairwise clustering

@article{Agarwal2005BeyondPC,
  title={Beyond pairwise clustering},
  author={Sameer Agarwal and Jongwoo Lim and Lihi Zelnik-Manor and Pietro Perona and David J. Kriegman and Serge J. Belongie},
  journal={2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05)},
  year={2005},
  volume={2},
  pages={838-845 vol. 2}
}
We consider the problem of clustering in domains where the affinity relations are not dyadic (pairwise), but rather triadic, tetradic or higher. The problem is an instance of the hypergraph partitioning problem. We propose a two-step algorithm for solving this problem. In the first step we use a novel scheme to approximate the hypergraph using a weighted graph. In the second step a spectral partitioning algorithm is used to partition the vertices of this graph. The algorithm is capable of… CONTINUE READING
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