Interesting comparison, but only using generated mixtures of gaussians for training data severely limits any conclusions that can be drawn from this. Naturally the method with the same assumptions as the generating process had the best performance.

It is important to note that both the performance of the machine learning algorithm (in terms of the error metric) and its runtime are very dependent on the source data in most cases.