mlsanityData to 14 Oct 2026

Only distances are required to reconstruct submanifolds

arXiv 1410.7012 ↗First posted 26 Oct 2014cs.CGcited by 1

Not on the map. Why?

Abstract (arXiv)

In this paper, we give the first algorithm that outputs a faithful reconstruction of a submanifold of Euclidean space without maintaining or even constructing complicated data structures such as Voronoi diagrams or Delaunay complexes. Our algorithm uses the witness complex and relies on the stability of power protection, a notion introduced in this paper. The complexity of the algorithm depends exponentially on the intrinsic dimension of the manifold, rather than the dimension of ambient space, and linearly on the dimension of the ambient space. Another interesting feature of this work is that no explicit coordinates of the points in the point sample is needed. The algorithm only needs the distance matrix as input, i.e., only distance between points in the point sample as input.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 26 Oct 2014.

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