Low-rank matrix factorization with attributes

We develop a new collaborative filtering (CF) method that combines both previously known users' preferences, i.e. standard CF, as well as product/user attributes, i.e. classical function approximation, to predict a given user's interest in a particular product. Our method is a generalized low rank matrix completion problem, where we learn a function whose inputs are pairs of vectors

• Type: Journal
• Year: 2006
• Where: CORR
• Authors: Jacob Abernethy, Francis Bach, Theodoros Evgeniou, Jean-Philippe Vert
• Keywords: CORR 2006, Education, Matrix Completion, Matrix Completion Problem, Rank Matrix Completion