LUPA LAB

We are exploring collective approaches (that exploit collections like sets and distributions) to bridge the gap between machine and human learning by providing further context than myopic point estimation approaches. We prefer simple estimators that make few assumptions; that is, flexible and powerful methods that are able to generalize and extrapolate. Further, we are developing techniques for analyzing massive datasets, both in terms of instances and covariates.