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» Learning Mixtures of Gaussians
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ICIP
2010
IEEE
15 years 3 months ago
Entropies and cross-entropies of exponential families
Statistical modeling of images plays a crucial role in modern image processing tasks like segmentation, object detection and restoration. Although Gaussian distributions are conve...
Frank Nielsen, Richard Nock
ICASSP
2011
IEEE
14 years 10 months ago
Factored covariance modeling for text-independent speaker verification
Gaussian mixture models (GMMs) are commonly used to model the spectral distribution of speech signals for text-independent speaker verification. Mean vectors of the GMM, used in c...
Eryu Wang, Kong-Aik Lee, Bin Ma, Haizhou Li, Wu Gu...
ICML
2009
IEEE
16 years 7 months ago
Exploiting sparse Markov and covariance structure in multiresolution models
We consider Gaussian multiresolution (MR) models in which coarser, hidden variables serve to capture statistical dependencies among the finest scale variables. Tree-structured MR ...
Myung Jin Choi, Venkat Chandrasekaran, Alan S. Wil...
ICML
2002
IEEE
16 years 7 months ago
Diffusion Kernels on Graphs and Other Discrete Input Spaces
The application of kernel-based learning algorithms has, so far, largely been confined to realvalued data and a few special data types, such as strings. In this paper we propose a...
Risi Imre Kondor, John D. Lafferty
ICML
2006
IEEE
16 years 7 months ago
Efficient learning of Naive Bayes classifiers under class-conditional classification noise
We address the problem of efficiently learning Naive Bayes classifiers under classconditional classification noise (CCCN). Naive Bayes classifiers rely on the hypothesis that the ...
Christophe Nicolas Magnan, François Denis, ...