Learning to Learn and Collaborative Filtering
نویسندگان
چکیده
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 lowrank matrix approximation. This connection suggests to build a more general nonparametric approach to collaborative preference learning that additionally explores the content features of items.
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