Online k-MLE for mixture modelling with exponential families
نویسندگان
چکیده
منابع مشابه
Online k-MLE for Mixture Modeling with Exponential Families
This paper address the problem of online learning finite statistical mixtures of exponential families. A short review of the Expectation-Maximization (EM) algorithm and its online extensions is done. From these extensions and the description of the k-Maximum Likelihood Estimator (k-MLE), three online extensions are proposed for this latter. To illustrate them, we consider the case of mixtures o...
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We describe a novel algorithm called k-Maximum Likelihood Estimator (k-MLE) for learning finite statistical mixtures of exponential families relying on Hartigan’s k-means swap clustering method. To illustrate this versatile Hartigan k-MLE technique, we consider the exponential family of Wishart distributions and show how to learn their mixtures. First, given a set of symmetric positive definite...
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We introduce a novel algorithm to learn mixtures of Gamma distributions. This is an extension of the k-Maximum Likelihood estimator algorithm for mixtures of exponential families. Although Gamma distributions are exponential families, we cannot rely directly on the exponential families tools due to the lack of closed-form formula and the cost of numerical approximation: our method uses Gamma di...
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We describe an original implementation of k-Maximum Likelihood Estimator (k-MLE)[1], a fast algorithm for learning finite statistical mixtures of exponential families. Our version converges to a local maximum of the complete likelihood while guaranteeing not to have empty clusters. To initialize k-MLE, we propose a careful and greedy strategy inspired by k-means++ which selects automatically cl...
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Exponential families arise naturally in statistical modelling and the maximum likelihood estimate (MLE) is consistent and asymptotically normal for these models [Berk [2]]. In practice, often one needs to consider models with a large number of parameters, particularly if the sample size is large; see Huber [14], Haberman [13] and Portnoy [18 21]. One may also think that the true model can only ...
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تاریخ انتشار 2015