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ICML
2005
IEEE
15 years 10 months ago
Hierarchic Bayesian models for kernel learning
The integration of diverse forms of informative data by learning an optimal combination of base kernels in classification or regression problems can provide enhanced performance w...
Mark Girolami, Simon Rogers
ECCV
2002
Springer
15 years 11 months ago
Robust Computer Vision through Kernel Density Estimation
Abstract. Two new techniques based on nonparametric estimation of probability densities are introduced which improve on the performance of equivalent robust methods currently emplo...
Haifeng Chen, Peter Meer
ICPR
2010
IEEE
15 years 3 months ago
Online Discriminative Kernel Density Estimation
—We propose a new method for online estimation of probabilistic discriminative models. The method is based on the recently proposed online Kernel Density Estimation (oKDE) framew...
Matej Kristan, Ales Leonardis
ICPR
2006
IEEE
15 years 10 months ago
Adaptive Feature Integration for Segmentation of 3D Data by Unsupervised Density Estimation
In this paper, a novel unsupervised approach for the segmentation of unorganized 3D points sets is proposed. The method derives by the mean shift clustering paradigm devoted to se...
Marco Cristani, Umberto Castellani, Vittorio Murin...
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BCS
2008
14 years 11 months ago
Fast Estimation of Nonparametric Kernel Density Through PDDP, and its Application in Texture Synthesis
In this work, a new algorithm is proposed for fast estimation of nonparametric multivariate kernel density, based on principal direction divisive partitioning (PDDP) of the data s...
Arnab Sinha, Sumana Gupta