Divergence-Based Motivation for Online EM and Combining Hidden Variable Models

11 Feb 2019 Ehsan Amid Manfred K. Warmuth

Expectation-Maximization (EM) is a prominent approach for parameter estimation of hidden (aka latent) variable models. Given the full batch of data, EM forms an upper-bound of the negative log-likelihood of the model at each iteration and updates to the minimizer of this upper-bound... (read more)

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