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.
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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.