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» Dirichlet Process Mixtures of Generalized Linear Models
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163
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EMNLP
2010
14 years 12 months ago
Holistic Sentiment Analysis Across Languages: Multilingual Supervised Latent Dirichlet Allocation
In this paper, we develop multilingual supervised latent Dirichlet allocation (MLSLDA), a probabilistic generative model that allows insights gleaned from one language's data...
Jordan L. Boyd-Graber, Philip Resnik
151
Voted
TNN
2010
216views Management» more  TNN 2010»
14 years 8 months ago
Simplifying mixture models through function approximation
Finite mixture model is a powerful tool in many statistical learning problems. In this paper, we propose a general, structure-preserving approach to reduce its model complexity, w...
Kai Zhang, James T. Kwok
TNN
2008
128views more  TNN 2008»
15 years 1 months ago
A Hybrid Technique for Blind Separation of Non-Gaussian and Time-Correlated Sources Using a Multicomponent Approach
Blind inversion of a linear and instantaneous mixture of source signals is a problem often encountered in many signal processing applications. Efficient FastICA (EFICA) offers an ...
Petr Tichavský, Zbynek Koldovský, Ar...
BMCBI
2008
92views more  BMCBI 2008»
15 years 2 months ago
A semiparametric modeling framework for potential biomarker discovery and the development of metabonomic profiles
Background: The discovery of biomarkers is an important step towards the development of criteria for early diagnosis of disease status. Recently electrospray ionization (ESI) and ...
Samiran Ghosh, David F. Grant, Dipak K. Dey, Denni...
85
Voted
ICIP
2002
IEEE
16 years 3 months ago
Face recognition using mixtures of principal components
We introduce an efficient statistical modeling technique called Mixture of Principal Components (MPC). This model is a linear extension to the traditional Principal Component Anal...
Deepak S. Turaga, Tsuhan Chen