Space-Time Local Embeddings

Sun, Ke, Wang, Jun, Kalousis, Alexandros, Marchand-Maillet, Stephane

Neural Information Processing Systems 

Space-time is a profound concept in physics. This concept was shown to be useful for dimensionality reduction. We present basic definitions with interesting counter-intuitions.We give theoretical propositions to show that space-time is a more powerful representation than Euclidean space. We apply this concept to manifold learning for preserving local information. Empirical results on nonmetric datasetsshow that more information can be preserved in space-time.

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