We study a class of weakly identifiable location-scale mixture models for which the maximum likelihood estimates based on n i.i.d. samples are known to have ...
Feb 1, 2019 · Abstract:We study a class of weakly identifiable location-scale mixture models for which the maximum likelihood estimates based on n i.i.d. ...
The focus of this paper is the intersection of statistical and computational issues associated with fitting the parameters of weakly identifiable mixture models ...
Sharp Analysis of Expectation-Maximization for Weakly Identifiable Models ... Sharp Analysis of Expectation-Maximization for Weakly Identifiable Models sample ...
We study a class of weakly identifiable location-scale mixture models for which the maximum likelihood estimates based on $n$ i.i.d. samples are known to ...
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Sharp Analysis of Expectation-Maximization for Weakly Identifiable Models. R ... Theoretical guarantees for EM under misspecified Gaussian mixture models. R ...
Sharp Analysis of Expectation-Maximization for Weakly Identifiable Models ... We study a class of weakly identifiable location-scale mixture models for which the ...
Specific areas include EM algorithm, Gaussian mixture models, model mis-specification, factor analysis ... Sharp Analysis of Expectation-Maximization for Weakly ...
Sharp Analysis of Expectation-Maximization for Weakly Identifiable Models ... 2020. TLDR. A rigorous characterization of EM for fitting a weakly identifiable ...