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NIPS
2004
13 years 8 months ago
Sampling Methods for Unsupervised Learning
We present an algorithm to overcome the local maxima problem in estimating the parameters of mixture models. It combines existing approaches from both EM and a robust fitting algo...
Robert Fergus, Andrew Zisserman, Pietro Perona
ECCV
2010
Springer
14 years 10 days ago
Single Image Deblurring Using Motion Density Functions
Abstract. We present a novel single image deblurring method to estimate spatially non-uniform blur that results from camera shake. We use existing spatially invariant deconvolution...
BMCBI
2011
13 years 2 months ago
A novel approach to the clustering of microarray data via nonparametric density estimation
Background: Cluster analysis is a crucial tool in several biological and medical studies dealing with microarray data. Such studies pose challenging statistical problems due to di...
Riccardo De Bin, Davide Risso
TIP
2002
179views more  TIP 2002»
13 years 6 months ago
Unsupervised image classification, segmentation, and enhancement using ICA mixture models
An unsupervised classification algorithm is derived by modeling observed data as a mixture of several mutually exclusive classes that are each described by linear combinations of i...
Te-Won Lee, Michael S. Lewicki
IDA
2009
Springer
14 years 1 months ago
Estimating Squared-Loss Mutual Information for Independent Component Analysis
Abstract. Accurately evaluating statistical independence among random variables is a key component of Independent Component Analysis (ICA). In this paper, we employ a squared-loss ...
Taiji Suzuki, Masashi Sugiyama