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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| フォーマット: | Conference item |
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Massachusetts Institute of Technology Press
2018
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