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NIPS
2004

Maximum-Margin Matrix Factorization

9 years 22 days ago
Maximum-Margin Matrix Factorization
We present a novel approach to collaborative prediction, using low-norm instead of low-rank factorizations. The approach is inspired by, and has strong connections to, large-margin linear discrimination. We show how to learn low-norm factorizations by solving a semi-definite program, and discuss generalization error bounds for them.
Nathan Srebro, Jason D. M. Rennie, Tommi Jaakkola
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2004
Where NIPS
Authors Nathan Srebro, Jason D. M. Rennie, Tommi Jaakkola
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