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ICML
2008
IEEE
16 years 4 months ago
Estimating local optimums in EM algorithm over Gaussian mixture model
EM algorithm is a very popular iteration-based method to estimate the parameters of Gaussian Mixture Model from a large observation set. However, in most cases, EM algorithm is no...
Zhenjie Zhang, Bing Tian Dai, Anthony K. H. Tung
ALT
2003
Springer
16 years 1 months ago
Kernel Trick Embedded Gaussian Mixture Model
In this paper, we present a kernel trick embedded Gaussian Mixture Model (GMM), called kernel GMM. The basic idea is to embed kernel trick into EM algorithm and deduce a parameter ...
Jingdong Wang, Jianguo Lee, Changshui Zhang
ICPR
2008
IEEE
15 years 10 months ago
Boosting Gaussian mixture models via discriminant analysis
The Gaussian mixture model (GMM) can approximate arbitrary probability distributions, which makes it a powerful tool for feature representation and classification. However, it su...
Hao Tang, Thomas S. Huang
ICRA
2008
IEEE
142views Robotics» more  ICRA 2008»
15 years 10 months ago
Gaussian mixture models for probabilistic localization
— One of the key tasks during the realization of probabilistic approaches to localization is the design of a proper sensor model, that calculates the likelihood of a measurement ...
Patrick Pfaff, Christian Plagemann, Wolfram Burgar...
ICMCS
2005
IEEE
145views Multimedia» more  ICMCS 2005»
15 years 9 months ago
Gaussian Mixture Modeling Using Short Time Fourier Transform Features for Audio Fingerprinting
In audio fingerprinting, an audio clip must be recognized by matching an extracted fingerprint to a database of previously computed fingerprints. The fingerprints should reduc...
Arunan Ramalingam, Sridhar Krishnan