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EGITALY
2006
13 years 10 months ago
3D Data Segmentation Using a Non-Parametric Density Estimation Approach
In this paper, a new segmentation approach for sets of 3D unorganized points is proposed. The method is based on a clustering procedure that separates the modes of a non-parametri...
Umberto Castellani, Marco Cristani, Vittorio Murin...
NIPS
2004
13 years 10 months ago
The Laplacian PDF Distance: A Cost Function for Clustering in a Kernel Feature Space
A new distance measure between probability density functions (pdfs) is introduced, which we refer to as the Laplacian pdf distance. The Laplacian pdf distance exhibits a remarkabl...
Robert Jenssen, Deniz Erdogmus, José Carlos...
NIPS
2004
13 years 10 months ago
Outlier Detection with One-class Kernel Fisher Discriminants
The problem of detecting "atypical objects" or "outliers" is one of the classical topics in (robust) statistics. Recently, it has been proposed to address this...
Volker Roth
SDM
2010
SIAM
165views Data Mining» more  SDM 2010»
13 years 10 months ago
Direct Density Ratio Estimation with Dimensionality Reduction
Methods for directly estimating the ratio of two probability density functions without going through density estimation have been actively explored recently since they can be used...
Masashi Sugiyama, Satoshi Hara, Paul von Büna...
ISBI
2008
IEEE
14 years 9 months ago
Coupled nonparametric shape priors for segmentation of multiple basal ganglia structures
This paper presents a new method for multiple structure segmentation, using a maximum a posteriori (MAP) estimation framework, based on prior shape densities involving nonparametr...
Aytül Erçil, Gozde B. Unal, Müjda...