Browsing Computer Science and Artificial Intelligence Lab (CSAIL) by Subject "EM algorithm"
Now showing items 1-4 of 4
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Fast Learning by Bounding Likelihoods in Sigmoid Type Belief Networks
(1996-02-09)Sigmoid type belief networks, a class of probabilistic neural networks, provide a natural framework for compactly representing probabilistic information in a variety of unsupervised and supervised learning problems. ...
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Learning from Incomplete Data
(1995-01-24)Real-world learning tasks often involve high-dimensional data sets with complex patterns of missing features. In this paper we review the problem of learning from incomplete data from two statistical perspectives---the ...
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A Note on the Generalization Performance of Kernel Classifiers with Margin
(2000-05-01)We present distribution independent bounds on the generalization misclassification performance of a family of kernel classifiers with margin. Support Vector Machine classifiers (SVM) stem out of this class of machines. The ...
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On Convergence Properties of the EM Algorithm for Gaussian Mixtures
(1995-04-21)"Expectation-Maximization'' (EM) algorithm and gradient-based approaches for maximum likelihood learning of finite Gaussian mixtures. We show that the EM step in parameter space is obtained from the gradient via a ...