Stochastic expectation maximization with variance reduction

Stochastic expectation maximization with variance reduction

Expectation-Maximization (EM) is a popular tool for learning latent variable models, but the vanilla batch EM does not scale to large data sets because the whole data set is needed at every E-step. Stochastic Expectation Maximization (sEM) reduces the cost of E-step by stochastic approximation. Howe...

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Bibliografische gegevens
Hoofdauteurs:	Chen, J, Zhu, J, Teh, Y, Zhang, T
Formaat:	Conference item
Gepubliceerd in:	Massachusetts Institute of Technology Press 2018

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