Towards scalable Bayesian nonparametric methods for data analytics

Resorting big data to actionable information involves dealing with four dimensions of challenges in big data (called four V’s): volume, variety, velocity, veracity. In this study, we seek for novel Bayesian nonparametric models and scalable learning algorithms which can deal with these challenges of the big data era.