Expanding the Role of Mixture Models in Statistical Analyses of Big Data (2017-2020)

The project considers the challenge of developing theoretically sound procedures needed to scale inference and learning algorithms to allow the analysis of so-called big data sets. New data analytic tools and algorithms are to be developed for the analysis of big data sets to which classical methods of inference cannot be applied directly due to either the complexity of the data set or its sheer size. A key aspect is the development of new algorithms to enable the application of the new or appropriately modified existing inferential procedures to complex and large data sets. Such applications will lead to breakthrough discoveries and innovation in science, engineering, medicine, commerce, education, and national security.