Statistical Machine Learning Lab

Statistics and Machine Learning are two fields that solve similar problems, although each of them has its own paradigm. Thus, the tools used by these communities often have a different nature. The spirit of this research group is to take the best of both worlds, combining them so as to create improved solutions to relevant real-world problems.

Our work includes both theoretical and applied research. From a methological perspective, we are currently interested in nonparametric inference, recommender systems, high-dimensional statistics, Bayesian methods, predictive inference, and hypothesis tests. Our applications include genetics, cosmology and linguistics.