Desingularization of Bounded-Rank Matrix Sets

DOI10.1137/16M1108194zbMath1453.65095arXiv1612.03973OpenAlexW2962782032MaRDI QIDQ5373921

Valentin Khrulkov, Ivan V. Oseledets

Publication date: 6 April 2018

Published in: SIAM Journal on Matrix Analysis and Applications (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1612.03973

zbMATH Keywords

geometryoptimizationcompletionmatrixalgebraiclow-rank matricesRiemannian

Mathematics Subject Classification ID

Eigenvalues, singular values, and eigenvectors (15A18) Numerical linear algebra (65F99)

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Uses Software

• Macaulay2
• Pymanopt
• MovieLens

Cites Work

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• A Riemannian Gradient Sampling Algorithm for Nonsmooth Optimization on Manifolds
• Numerical solution of saddle point problems
• Newton’s Method at Singular Points. II
• On a Problem of Weighted Low-Rank Approximation of Matrices
• The Power of Convex Relaxation: Near-Optimal Matrix Completion
• Dynamical Low‐Rank Approximation
• The Rotation of Eigenvectors by a Perturbation. III
• Preconditioned Low-rank Riemannian Optimization for Linear Systems with Tensor Product Structure

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