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Manifold learning subsumes techniques conceived for problems where data of interest are assumed to lie on an embedded non-linear manifold within a higher-dimensional space.

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Do any dimensionality reduction techniques find embeddings which optimally preserve the K-nearest neighbors of each point? If no algorithm provably does this, are there algorithms which heuristically …
asked Mar 7 by user2663116