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Low-rank approximation with zeros aims to find a matrix of fixed rank and with a fixed zero pattern that minimizes the Euclidean distance to a given data matrix. We study… Click to show full abstract
Low-rank approximation with zeros aims to find a matrix of fixed rank and with a fixed zero pattern that minimizes the Euclidean distance to a given data matrix. We study the critical points of this optimization problem using algebraic tools. In particular, we describe special linear, affine and determinantal relations satisfied by the critical points. We also investigate the number of critical points and how the number is related to the complexity of nonnegative matrix factorization problem.
Keywords:
rank;
rank approximation;
approximation zeros;
low rank
Journal Title: Linear Algebra and its Applications
Year Published: 2022
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Journal Title: Linear Algebra and its Applications
Year Published: 2022
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!