Learning to learn and collaborative filtering
This paper reviews several recent multi-task learning algorithms in a general framework. Interestingly, the framework establishes a connection to recent collaborative filtering algorithms using low-rank matrix approximation. This connection suggests to build a more general nonparametric approach to collaborative preference learning that additionally explores the content features of items.