NeurIPS 2015
Space-Time Local Embeddings
Abstract
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.
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Keywords
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Context
- Venue
- Annual Conference on Neural Information Processing Systems
- Archive span
- 1987-2025
- Indexed papers
- 30776
- Paper id
- 842200680141057050