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» Sparse Representation for Gaussian Process Models
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ICASSP
2009
IEEE
13 years 5 months ago
Blind sparse source separation for unknown number of sources using Gaussian mixture model fitting with Dirichlet prior
In this paper, we propose a novel sparse source separation method that can be applied even if the number of sources is unknown. Recently, many sparse source separation approaches ...
Shoko Araki, Tomohiro Nakatani, Hiroshi Sawada, Sh...
ICIP
2007
IEEE
14 years 9 months ago
Faithful Shape Representation for 2D Gaussian Mixtures
It has been recently discovered that a faithful representation for the shape of some simple distributions can be constructed using invariant statistics [1, 2]. In this paper, we c...
Mireille Boutin, Mary I. Comer
ICASSP
2011
IEEE
12 years 11 months ago
Soft frame margin estimation of Gaussian Mixture Models for speaker recognition with sparse training data
—Discriminative Training (DT) methods for acoustic modeling, such as MMI, MCE, and SVM, have been proved effective in speaker recognition. In this paper we propose a DT method fo...
Yan Yin, Qi Li
ICPR
2010
IEEE
13 years 12 months ago
Microaneurysm (MA) Detection Via Sparse Representation Classifier with MA and Non-MA Dictionary Learning
Diabetic retinopathy (DR) is a common complication of diabetes that damages the retina and leads to sight loss if treated late. In its earliest stage, DR can be diagnosed by microa...
Bob Zhang, Lei Zhang, Jane You, Fakhri Karray
CDC
2009
IEEE
157views Control Systems» more  CDC 2009»
14 years 7 days ago
On trajectory optimization for active sensing in Gaussian process models
Abstract— We consider the problem of optimizing the trajectory of a mobile sensor with perfect localization whose task is to estimate a stochastic, perhaps multidimensional fiel...
Jerome Le Ny, George J. Pappas