Systems | Information | Learning | Optimization

Functional Nuclear Norm and Low Rank Function Estimation

The problem of low rank estimation naturally arises in a number of functional or relational data analysis settings, for example when dealing with spatio-temporal data or link prediction with attributes. We consider a unified framework for these problems and devise a novel penalty function to exploit the low rank structure in such contexts. The resulting empirical risk minimization estimator can be shown to be optimal under fairly general conditions.
January 22 @ 13:00
1:00 pm (1h)

Discovery Building, Orchard View Room

Ming Yuan