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Recall that in the implementation of the proposed convex method, CVX2, each boosting step (which adds a single rank to the solution) is interleaved with local optimization. For the local optimization we use a standard LBFGS implementation with default termination conditions. For the outer boosting iterations we terminate when the relative objective improvement is less than 5e-5 or the absolute improvement is less than 1e-3. The average rank results in the above table corresponds to the number of boosting rounds used by CVX2, which also determines the rank of its final solutions. From these results, one can see that the method uses significantly less than the full O(t 2) storage.