GW-MDS reformulates multidimensional scaling as a Gromov-Wasserstein minimization problem and shows embeddings whose pairwise distances correlate with the original ones comparably to MDS and Isomap.
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A dimensionality reduction technique based on the Gromov-Wasserstein distance
GW-MDS reformulates multidimensional scaling as a Gromov-Wasserstein minimization problem and shows embeddings whose pairwise distances correlate with the original ones comparably to MDS and Isomap.