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Poster
Space-Time Local Embeddings
Ke SUN · Jun Wang · Alexandros Kalousis · Stephane Marchand-Maillet
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 non-metric datasets show that more information can be preserved in space-time.
Author Information
Ke SUN (University of Geneva)
Jun Wang (Expedia, Geneva)
Alexandros Kalousis
Stephane Marchand-Maillet (University of Geneva)
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