Matrix Completion from Noisy Entries

NeurIPS 2009 Raghunandan H. KeshavanAndrea MontanariSewoong Oh

Given a matrix M of low-rank, we consider the problem of reconstructing it from noisy observations of a small, random subset of its entries. The problem arises in a variety of applications, from collaborative filtering (the `Netflix problem') to structure-from-motion and positioning... (read more)

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