Structure preserving embedding

@inproceedings{Shaw2009StructurePE,
  title={Structure preserving embedding},
  author={B. Shaw and T. Jebara},
  booktitle={ICML '09},
  year={2009}
}
Structure Preserving Embedding (SPE) is an algorithm for embedding graphs in Euclidean space such that the embedding is low-dimensional and preserves the global topological properties of the input graph. Topology is preserved if a connectivity algorithm, such as k-nearest neighbors, can easily recover the edges of the input graph from only the coordinates of the nodes after embedding. SPE is formulated as a semidefinite program that learns a low-rank kernel matrix constrained by a set of linear… Expand
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References

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Nonlinear Dimensionality Reduction by Semidefinite Programming and Kernel Matrix Factorization
Training structural SVMs when exact inference is intractable
Asymptotic expansions of the k nearest neighbor risk