Online k-MLE for mixture modeling with exponential families - Christophe Saint-Jean, Frank Nielsen
Author(s): Christophe Saint-Jean, Frank Nielsen
DOI URL: http://dx.doi.org/10.1007/978-3-319-25040-3_37
Slides: Saint-Jean_Online kMLE.pdf
Creative Commons Attribution-ShareAlike 4.0 International
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 of Wishart distributions by giving details and providing some experiments.