This paper deals with a nonparametric method for estimating the ridges of a density function. Ridge estimation is useful for understanding the structure of a density. It can also be used to find hidden structure in point cloud data: when the data are noisy measurements of a manifold, under mild conditions the ridges are close and topologically similar to the hidden manifold. We propose a new estimation procedure called SuRF and study its rate of convergence.

SuRF: Subspace Ridge Finder / PERONE PACIFICO, Marco. - STAMPA. - (2013), pp. 357-360.

SuRF: Subspace Ridge Finder

PERONE PACIFICO, Marco
2013

Abstract

This paper deals with a nonparametric method for estimating the ridges of a density function. Ridge estimation is useful for understanding the structure of a density. It can also be used to find hidden structure in point cloud data: when the data are noisy measurements of a manifold, under mild conditions the ridges are close and topologically similar to the hidden manifold. We propose a new estimation procedure called SuRF and study its rate of convergence.
2013
mean shift; manifold learning; ridges; density estimation
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
SuRF: Subspace Ridge Finder / PERONE PACIFICO, Marco. - STAMPA. - (2013), pp. 357-360.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/548678
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