A Dictionary Learning Approach for Factorial Gaussian Models

no code implementations • 18 Aug 2015 • Y. Cem Subakan, Johannes Traa, Paris Smaragdis, Noah Stein

We argue that due to the specific structure of the activation matrix $R$ in the shared component factorial mixture model, and an incoherence assumption on the shared component, it is possible to extract the columns of the $O$ matrix without the need for alternating between the estimation of $O$ and $R$.

Dictionary Learning