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Spectral Regularization Algorithms for Learning Large Incomplete Matrices
We use convex relaxation techniques to provide a sequence of regularized low-rank solutions for large-scale matrix completion problems. Using the nuclear norm as a regularizer, we provide a simple and very efficient convex algorithm for minimizing the reconstruction error subject to a bound on the n...
שמור ב:
| Main Authors: | , , |
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| פורמט: | Artigo |
| שפה: | Inglês |
| יצא לאור: |
2010
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| נושאים: | |
| גישה מקוונת: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3087301/ https://ncbi.nlm.nih.gov/pubmed/21552465 |
| תגים: |
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