Paper Info
Title
On the equivalence between low rank matrix completion and tensor rank.
Abstract
The Rank Minimization Problem asks to find a matrix of lowest rank inside a linear variety of the space of n x n matrices. The Low Rank Matrix Completion problem asks to complete a partially filled matrix such that the resulting matrix has smallest possible rank. The Tensor Rank Problem asks to determine the rank of a tensor. We show that these three problems are equivalent: each one of the problems can be reduced to the other two.
Year
Venue
Field
2014
CoRR
Rank (linear algebra),Tensor product,Discrete mathematics,Combinatorics,Matrix (mathematics),Rank (graph theory),Mean reciprocal rank,Low-rank approximation,Gaussian elimination,Rank of an abelian group,Mathematics
DocType
Volume
Citations 
Journal
abs/1406.0080
0
PageRank 
References 
Authors
0.34
16
1
Name
Order
Citations
PageRank
Harm Derksen115115.00