Collaborative Filtering with Graph Information: Consistency and Scalable Methods
Annual Conference on Neural Information Processing Systems, 2015.
Low rank matrix completion plays a fundamental role in collaborative filtering applications, the key idea being that the variables lie in a smaller subspace than the ambient space. Often, additional information about the variables is known, and it is reasonable to assume that incorporating this information will lead to better predictions....More
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