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ICASSP
2009
IEEE
14 years 2 months ago
A complex cross-spectral distribution model using Normal Variance Mean Mixtures
We propose a model for the density of cross-spectral coefficients using Normal Variance Mean Mixtures. We show that this model density generalizes the corresponding marginal dens...
Jason A. Palmer, Scott Makeig, Kenneth Kreutz-Delg...
CSDA
2007
202views more  CSDA 2007»
13 years 8 months ago
Bayesian estimation of the Gaussian mixture GARCH model
In this paper, we perform Bayesian inference and prediction for a GARCH model where the innovations are assumed to follow a mixture of two Gaussian distributions. This GARCH model...
María Concepción Ausín, Pedro...
AIPR
2002
IEEE
14 years 27 days ago
ICA Mixture Model based Unsupervised Classification of Hyperspectral Imagery
Conventional remote sensing classification techniques that model the data in each class with a multivariate Gaussian distribution are inefficient, as this assumption is generally ...
Chintan A. Shah, Manoj K. Arora, Stefan A. Robila,...
IJON
2011
186views more  IJON 2011»
12 years 11 months ago
Discriminative structure selection method of Gaussian Mixture Models with its application to handwritten digit recognition
, Yunde Jia Model structure selection is currently an open problem in modeling data via Gaussian Mixture Models (GMM). This paper proposes a discriminative method to select GMM st...
Xuefeng Chen, Xiabi Liu, Yunde Jia
KDD
2004
ACM
136views Data Mining» more  KDD 2004»
14 years 8 months ago
A cross-collection mixture model for comparative text mining
In this paper, we define and study a novel text mining problem, which we refer to as Comparative Text Mining (CTM). Given a set of comparable text collections, the task of compara...
ChengXiang Zhai, Atulya Velivelli, Bei Yu