Literature DB >> 12662630

On the identifiability of mixtures-of-experts.

W Jiang1, M A. Tanner.   

Abstract

In mixtures-of-experts (ME) models, "experts" of generalized linear models are combined, according to a set of local weights called the "gating function". The invariant transformations of the ME probability density functions include the permutations of the expert labels and the translations of the parameters in the gating functions. Under certain conditions, we show that the ME systems are identifiable if the experts are ordered and the gating parameters are initialized. The conditions are validated for Poisson, gamma, normal and binomial experts.

Year:  1999        PMID: 12662630     DOI: 10.1016/s0893-6080(99)00066-0

Source DB:  PubMed          Journal:  Neural Netw        ISSN: 0893-6080


  2 in total

1.  The impact of covariance misspecification in multivariate Gaussian mixtures on estimation and inference: an application to longitudinal modeling.

Authors:  Brianna C Heggeseth; Nicholas P Jewell
Journal:  Stat Med       Date:  2013-01-07       Impact factor: 2.373

2.  Whole-Volume Clustering of Time Series Data from Zebrafish Brain Calcium Images via Mixture Modeling.

Authors:  Hien D Nguyen; Jeremy F P Ullmann; Geoffrey J McLachlan; Venkatakaushik Voleti; Wenze Li; Elizabeth M C Hillman; David C Reutens; Andrew L Janke
Journal:  Stat Anal Data Min       Date:  2017-12-06       Impact factor: 1.051

  2 in total

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