Collaborative Filtering in a Non-Uniform World: Learning with the Weighted Trace Norm

Details Collaborative Filtering in a Non-Uniform World: Learning with the Weighted Trace Norm Collaborative Filtering in a Non-Uniform World: Learning with the Weighted Trace Norm

2010-02-14

arxiv.org/abs/1002.2780v1

Computer Science

Learning

9 pages

Scientific paper

We show that matrix completion with trace-norm regularization can be significantly hurt when entries of the matrix are sampled non-uniformly. We introduce a weighted version of the trace-norm regularizer that works well also with non-uniform sampling. Our experimental results demonstrate that the weighted trace-norm regularization indeed yields significant gains on the (highly non-uniformly sampled) Netflix dataset.

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