GMM

(redirected from Gaussian mixture model)
AcronymDefinition
GMMGood Mythical Morning
GMMGaussian Mixture Model
GMMGeneralized Method of Moments (economics)
GMMGeneral Membership Meeting
GMMGPRS Mobility Management
GMMGeneral Merchandise Manager (job title)
GMMGlobal Management and Manufacturing (degree; Denmark)
GMMGlobal Marijuana March
GMMGlobal Market Manager (various companies)
GMMGeneral Maintenance Manual
GMMGenetically Modified Microorganisms
GMMGimar Montaz Mautino (French ski equipment company)
GMMGeorge Mason Mortgage (Fairfax, VA)
GMMGive Me Money
GMMGiovanotti Mondani Meccanici (Italian multimedia artistic group)
GMMGood Mobile Messaging
GMMGenetically Modified Mosquito
GMMGlobal Money Market
GMMGeneral Maintenance Mechanic (various organizations)
GMMGraspop Metal Meeting (music festival, Belgium)
GMMGaribaldi-Meucci Museum (New York, NY)
GMMGrand Mesa Music (Grand Junction, CO)
GMMGlobal Multimedia Mobility
GMMGlobal Materials Management (various businesses)
GMMGlobal Movement Management
GMMGospel Music Ministries (Alaska)
GMMGram Molecular Mass (chemistry)
GMMGeometric Math Model
GMMGCDB Measurement Management
GMMGEC-Marconi Materials Technology
GMMGeneral Management Meeting
GMM(USN Rating) Gunner's Mate (Missiles)
GMMGross Money Multiple (finance)
References in periodicals archive ?
In this experiment, we evaluate our method by cooperating with Gaussian mixture models (GMMs), which is a standard model for image representation, for image recognition.
Improved adaptive Gaussian mixture model for back-ground subtraction," in Proc.
Keywords: Clustering, Expected Maximization, Gaussian Mixture Model, Maximum Likelihood
The multivariate gaussian mixture model for abnormality-enhanced visualization was proposed by Grim et al.
We propose a regression approach based on Gaussian Mixture Models for building energy prediction and uncertainty quantification that has the following advantages (1) response surface modeling is integrated with local uncertainty quantification, therefore a secondary process of localized or global confidence estimation does not need to be performed (2) impact of correlated regressors is low in this approach (3) sensitivity to sparse data density is low, and (4) there is a principled approach to model structure selection as opposed to being based purely on domain knowledge.
The benefit of the achieved relevant zone maps is tested in an acoustic-to-articulatory regression system based on Gaussian mixture models (GMMs).
A Gaussian mixture model (GMM) is a weighted combination of Gaussian probability density functions.
Keywords: Wireless sensor networks, localization algorithms, non-localizable problem, Gaussian mixture model, collaborative and predictive schemes
1], Hidden Markov model (HMM) [2], Gaussian mixture model (GMM) [3], Harmonic Noise Model (HNM) [4].
At that time only the Gaussian mixture model was replaced with a deep neural network (DNN), keeping everything else the same.
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