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Gaussian Component Based Index for GMMs
2016 IEEE 16th International Conference on Data Mining (ICDM), 2016Efficient similarity search for uncertain data is a challenging task in many modern data mining applications like image retrieval, speaker recognition and stock market analysis. A common way to model the uncertainty of data objects is using probability density functions in the form of Gaussian Mixture Models (GMMs), which have an ability to approximate
Zhou, Linfei +4 more
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Detecting Invalid Instruments Using L1-GMM
SSRN Electronic Journal, 2007zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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An improved voice conversion method using segmental GMMs and automatic GMM selection
2011 4th International Congress on Image and Signal Processing, 2011In this paper, the idea of segmental GMMs is proposed for voice conversion. Also, to apply this idea to on-line voice conversion, we have developed an automatic GMM selection algorithm based on dynamic programming. In addition, to map a vector of DCC (discrete cepstrum coefficients) with only one Gaussian mixture, we have designed a mixture selection ...
Hung-Yan Gu, Sung-Fung Tsai
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Tricks with Hicks: Stata GMM code for nonlinear gmm [PDF]
, 2011 In a June, 2009 American Economic Review article entitled "Tricks with Hicks: The EASI Demand System", Arthur Lewbel and Krishna Pendakur proposed the exact affine Stone index demand system. This system allows Engel curve behavior higher than rank 3, demographics, and unobserved heterogeneity in tastes.
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GMM-based SVM for face recognition
18th International Conference on Pattern Recognition (ICPR'06), 2006A new face recognition algorithm is presented. It supposes that a video sequence of a person is available both at enrollment and test time. During enrollment, a client Gaussian mixture model (GMM) is adapted from a world GMM using eigenface features extracted from each frame of the video.
Bredin, Hervé +2 more
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2001
For both consistency and asymptotic normality of the GMM estimator it is not necessary to assume that \(\hat \theta \) precisely minimizes the GMM objective function (2.1.6). Andrews (1997) points out that for Theorem 2 (consistency) \(\hat \theta \) is required to be within Op(1) of the global minimum and for Theorem 3 (asymptotic normality), \(\hat ...
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For both consistency and asymptotic normality of the GMM estimator it is not necessary to assume that \(\hat \theta \) precisely minimizes the GMM objective function (2.1.6). Andrews (1997) points out that for Theorem 2 (consistency) \(\hat \theta \) is required to be within Op(1) of the global minimum and for Theorem 3 (asymptotic normality), \(\hat ...
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, 2008 A brief introduction to estimating Generalized Method of Moments models in Stata, using the optimize() function in Mata, with applications to nonlinear IV models.
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