Structured low-rank approximation: optimization on matrix manifold approach
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Publication:2114475
DOI10.1007/s40819-021-01162-8zbMath1487.65049OpenAlexW3212964078MaRDI QIDQ2114475
Publication date: 15 March 2022
Published in: International Journal of Applied and Computational Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s40819-021-01162-8
Cites Work
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- A feasible method for optimization with orthogonality constraints
- A quadratically convergent algorithm for structured low-rank approximation
- Computing the radius of controllability for state space systems
- Cadzow's basic algorithm, alternating projections and singular spectrum analysis
- Structured low rank approximations of the sylvester resultant matrix for approximate GCDS of Bernstein basis polynomials
- Stochastic algorithms for solving structured low-rank matrix approximation problems
- Matrix computations.
- On approximate GCDs of univariate polynomials
- Manifold based low-rank regularization for image restoration and semi-supervised learning
- Generalized inverses: theory and computations
- Structured low rank approximation
- First order optimality conditions and steepest descent algorithm on orthogonal Stiefel manifolds
- ALORA: affine low-rank approximations
- Optimization challenges in the structured low rank approximation problem
- Approximate greatest common divisor of many polynomials, generalised resultants, and strength of approximation
- Structured Low-Rank Approximation with Missing Data
- Factorization Approach to Structured Low-Rank Approximation with Applications
- The Sylvester Resultant Matrix and Image Deblurring
- Convergence Results for Projected Line-Search Methods on Varieties of Low-Rank Matrices Via Łojasiewicz Inequality
- Approximate greatest common divisors of several polynomials with linearly constrained coefficients and singular polynomials
- Exact Solutions in Structured Low-Rank Approximation
- Generalized Inverses of Linear Transformations
- An Iterative Method for Computing the Generalized Inverse of an Arbitrary Matrix
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