A Simple Algorithm for Nuclear Norm Regularized Problems

  title={A Simple Algorithm for Nuclear Norm Regularized Problems},
  author={Martin Jaggi and Marek Sulovsk{\'y}},
Optimization problems with a nuclear norm regularization, such as e.g. low norm matrix factorizations, have seen many applications recently. We propose a new approximation algorithm building upon the recent sparse approximate SDP solver of (Hazan, 2008). The experimental efficiency of our method is demonstrated on large matrix completion problems such as the Netflix dataset. The algorithm comes with strong convergence guarantees, and can be interpreted as a first theoretically justified variant… CONTINUE READING
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