Maximum-Margin Matrix FactorizationDownload PDFOpen Website

2004, 00:00 (modified: 11 Nov 2022, 17:44)NIPS 2004Readers: Everyone
Abstract: 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.
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