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» Density Estimation: Nonparametric Techniques
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COLT
2004
Springer
14 years 2 months ago
Performance Guarantees for Regularized Maximum Entropy Density Estimation
Abstract. We consider the problem of estimating an unknown probability distribution from samples using the principle of maximum entropy (maxent). To alleviate overfitting with a v...
Miroslav Dudík, Steven J. Phillips, Robert ...
ICIP
2006
IEEE
14 years 10 months ago
Estimating Illumination Chromaticity via Kernel Regression
We propose a simple nonparametric linear regression tool, known as kernel regression (KR), to estimate the illumination chromaticity. We design a Gaussian kernel whose bandwidth i...
Vivek Agarwal, Andrei V. Gribok, Andreas Koschan, ...
ICPR
2006
IEEE
14 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...
ICML
2007
IEEE
14 years 9 months ago
Hierarchical maximum entropy density estimation
We study the problem of simultaneously estimating several densities where the datasets are organized into overlapping groups, such as a hierarchy. For this problem, we propose a m...
David M. Blei, Miroslav Dudík, Robert E. Sc...
CVPR
2008
IEEE
14 years 11 months ago
Generalised blurring mean-shift algorithms for nonparametric clustering
Gaussian blurring mean-shift (GBMS) is a nonparametric clustering algorithm, having a single bandwidth parameter that controls the number of clusters. The algorithm iteratively sh...
Miguel Á. Carreira-Perpiñán