Math 2.0

Linear and multilinear algebra; matrix theory Matrix equations and groups Problem

Matrix completion

Builds on MatrixRank of a matrixSingular value

Problem

Let FF be a field and let m,n≥1m, n \ge 1 be integers. Let Ω\Omega be a set of positions (i,j)(i, j) with 1≤i≤m1 \le i \le m and 1≤j≤n1 \le j \le n. For each (i,j)∈Ω(i, j) \in \Omega, let a value Mij∈FM_{ij} \in F be given. Find an m×nm \times n matrix XX over FF such that Xij=MijX_{ij} = M_{ij} for all (i,j)∈Ω(i, j) \in \Omega and the rank of XX is as small as possible.

Remarks

Without more structure the problem has no unique answer: the entries outside Ω\Omega can be anything, so one asks for the completion of lowest rank. Low-rank completion is NP-hard in general. Over ℝ\R, a standard relaxation replaces the rank by the nuclear norm, the sum of the singular values of XX, which gives a convex problem. Candès and Recht proved in 2009 that nuclear norm minimization recovers the unknown matrix exactly with high probability, under some conditions. The matrix must have low rank and satisfy an incoherence condition, and enough entries must be sampled at random. Other versions ask for a completion that is positive semidefinite, or that has another prescribed property.

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To understand this page from the ground up, read these 4 pages in order. The foundations come first.

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  1. Matrix concept
  2. Rank of a matrix concept
  3. Singular value concept
  4. Matrix completion problem

Further reading

  1. Web https://en.wikipedia.org/wiki/Matrix_completion
About this page
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AboutRank of a matrix
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Changed2 November 2026

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