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Learning with the Weighted Trace-norm under Arbitrary Sampling Distributions

NIPS, (2011): 2133-2141

Cited: 61|Views31
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Abstract

We provide rigorous guarantees on learning with the weighted trace-norm under arbitrary sampling distributions. We show that the standard weighted trace-norm might fail when the sampling distribution is not a product distribution (i.e. when row and column indexes are not selected independently), present a corrected variant for which we ...More

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