An accelerated alternating minimization algorithm is developed for low-rank matrix approximation in the Chebyshev norm, along with a proof that its limit points satisfy a new necessary optimality condition called 2-way alternance of rank r.
Budzinskiy , On the distance to low-rank matrices in the maximum norm , Linear Algebra and its Applications, 688 (2024), pp
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Accelerated alternating minimization algorithm for low-rank approximations in the Chebyshev norm
An accelerated alternating minimization algorithm is developed for low-rank matrix approximation in the Chebyshev norm, along with a proof that its limit points satisfy a new necessary optimality condition called 2-way alternance of rank r.