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ICASSP
2009
IEEE
15 years 9 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»
15 years 2 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
15 years 7 months 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»
14 years 5 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»
16 years 2 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