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KDD
2006
ACM
175views Data Mining» more  KDD 2006»
15 years 10 months ago
A mixture model for contextual text mining
Contextual text mining is concerned with extracting topical themes from a text collection with context information (e.g., time and location) and comparing/analyzing the variations...
Qiaozhu Mei, ChengXiang Zhai
116
Voted
ICASSP
2009
IEEE
14 years 7 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...
AIPR
2002
IEEE
15 years 2 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 1 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
116
Voted
ICASSP
2011
IEEE
14 years 1 months ago
Labeling skin tissues in ultrasound images using a generalized Rayleigh mixture model
This paper addresses the problem of estimating the statistical distribution of multiple-tissue non-stationary ultrasound images of skin. The distribution of multiple-tissue images...
Marcelo Pereyra, Nicolas Dobigeon, Hadj Batatia, J...