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SDM
2004
SIAM
218views Data Mining» more  SDM 2004»
13 years 11 months ago
Mixture Density Mercer Kernels: A Method to Learn Kernels Directly from Data
This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density e...
Ashok N. Srivastava
ICPR
2010
IEEE
14 years 4 months ago
Joint Image GMM and Shading MAP Estimation
We consider a simple statistical model of the image, in which the image is represented as a sum of two parts: one part is explained by an i.i.d. color Gaussian mixture and the oth...
Alexander Shekhovtsov, Vaclav Hlavac
JCST
2010
139views more  JCST 2010»
13 years 8 months ago
Dirichlet Process Gaussian Mixture Models: Choice of the Base Distribution
In the Bayesian mixture modeling framework it is possible to infer the necessary number of components to model the data and therefore it is unnecessary to explicitly restrict the n...
Dilan Görür, Carl Edward Rasmussen
IDEAL
2003
Springer
14 years 3 months ago
PCA Fuzzy Mixture Model for Speaker Identification
In this paper, we proposed the principal component analysis (PCA) fuzzy mixture model for speaker identification. A PCA fuzzy mixture model is derived from the combination of the P...
Younjeong Lee, Joohun Lee, Ki Yong Lee
IPM
2008
102views more  IPM 2008»
13 years 9 months ago
Fast exact maximum likelihood estimation for mixture of language model
Language modeling is an effective and theoretically attractive probabilistic framework for text information retrieval. The basic idea of this approach is to estimate a language mo...
Yi Zhang 0001, Wei Xu