Perspectives on CUR Decompositions

2019/07/29 by Hamm, Keaton, Huang, Longxiu · 6 citations
#FOS: Mathematics #Numerical Analysis (math.NA)

paper · doi:10.48550/arxiv.1907.12668

Abstract

This note discusses an interesting matrix factorization called the CUR Decomposition. We illustrate various viewpoints of this method by comparing and contrasting them in different situations. Additionally, we offer a new characterization of CUR decompositions which synergizes these viewpoints and shows that they are indeed the same in the exact decomposition case.

Cited by

• Generalized Interlacing Families: New Error Bounds for CUR Matrix Decompositions
• Low-rank cross approximation of function-valued tensors for reduced-order modeling of parametric PDEs
• A CUR Krylov Solver for Large-Scale Linear Matrix Equations
• An Adaptive CUR Algorithm and its Application to Reduced-Order Modeling of Random PDEs
• CUR Matrix Approximation through Convex Optimization for Feature Selection
• Matrices over a Hilbert space and their low-rank approximation

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