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pro vyhledávání: '"Canas, Guillermo D."'
Given a two-dimensional space endowed with a divergence function that is convex in the first argument, continuously differentiable in the second, and satisfies suitable regularity conditions at Voronoi vertices, we show that orphan-freedom (the absen
Externí odkaz:
http://arxiv.org/abs/1512.03589
We study the problem of estimating a manifold from random samples. In particular, we consider piecewise constant and piecewise linear estimators induced by k-means and k-flats, and analyze their performance. We extend previous results for k-means in
Externí odkaz:
http://arxiv.org/abs/1209.1121
Autor:
Canas, Guillermo D., Rosasco, Lorenzo
We study the problem of estimating, in the sense of optimal transport metrics, a measure which is assumed supported on a manifold embedded in a Hilbert space. By establishing a precise connection between optimal transport metrics, optimal quantizatio
Externí odkaz:
http://arxiv.org/abs/1209.1077
Autor:
Canas, Guillermo D.
Recently, simple conditions for well-behaved-ness of anisotropic Voronoi diagrams have been proposed. While these conditions ensure well-behaved-ness of two types of practical anisotropic Voronoi diagrams, as well as the geodesic-distance one, in any
Externí odkaz:
http://arxiv.org/abs/1202.0867
We describe conditions under which an appropriately-defined anisotropic Voronoi diagram of a set of sites in Euclidean space is guaranteed to be composed of connected cells in any number of dimensions. These conditions are natural for problems in opt
Externí odkaz:
http://arxiv.org/abs/1102.3670
We show that, under mild conditions on the underlying metric, duals of appropriately defined anisotropic Voronoi diagrams are embedded triangulations. Furthermore, they always triangulate the convex hull of the vertices, and have other properties tha
Externí odkaz:
http://arxiv.org/abs/1102.3673
Publikováno v:
arXiv
We study the problem of estimating a manifold from random samples. In particular, we consider piecewise constant and piecewise linear estimators induced by k-means and k-flats, and analyze their performance. We extend previous results for k-means in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od________88::0a97a55949c1205b852336355bb29b02
http://hdl.handle.net/1721.1/92317
http://hdl.handle.net/1721.1/92317
Publikováno v:
Proceedings of the Twenty-Eighth Annual Symposium Computational Geometry; 6/17/2012, p219-228, 10p
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