Gaussian mixture models have a rich history in statistics, perhaps first introduced by Karl Pearson in 1894 to explain asymmetry observed in data measured from a population of Naples' crabs. Their use in a wide range of applications include the areas of economics, engineering and genetics. A fundamental problem is to learn the defining model parameters from a sample, and possible solutions...