Sublinear Variational Optimization of Gaussian Mixture Models with Millions to Billions of Parameters

Sebastian Salwig, Till Kahlke, Florian Hirschberger +2

Gaussian Mixture Models (GMMs) range among the most frequently used models in machine learning. However, training large, general GMMs becomes computationally prohibitive for data s…