articleJun 1, 2009Closed access

Matrix completion from a few entries

Stanford University

Indexed incrossref

Abstract

Let M be an n¿ × n matrix of rank r ¿ n, and assume that a uniformly random subset E of its entries is observed. We describe an efficient algorithm that reconstructs M from |E| = O(r n) observed entries with relative root mean square error RMSE ¿ C(¿) (nr/|E|) 1/2 . Further, if r = O(1) and M is sufficiently unstructured, then it can be reconstructed exactly from |E| = O(n log n) entries. This settles (in the case of bounded rank) a question left open by Candes and Recht and improves over the guarantees for their reconstruction algorithm. The complexity of our algorithm is O(|E|r log n), which opens the way to its use for massive data sets. In the process of proving these statements, we obtain a generalization…

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661
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Authors

3

Topics & keywords

Keywords
  • Combinatorics
  • Rank (graph theory)
  • Generalization
  • Matrix (chemical analysis)
  • Bounded function
  • Mathematics
  • Binary logarithm
  • Discrete mathematics
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