Ming Yuan. Functional nuclear norm and low rank function estimation.
Ming Yuan
2016 Invited talk
in
Workshop: Adaptive and Scalable Nonparametric Methods in Machine Learning
in
Workshop: Adaptive and Scalable Nonparametric Methods in Machine Learning
Abstract
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.
Speaker
Ming Yuan
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