The Fréchet derivative of rank-truncated CUR is a sampling-induced oblique tangent projector, so perturbations in its kernel are removed to first order.
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BOOOM parametrizes Stiefel manifold optimization into Euclidean angle space using global Givens rotations and solves it with recursive modified pattern search for loss-agnostic black-box problems.
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Revisiting CUR Perturbation Analysis: A Local Tangent-Space Expansion
The Fréchet derivative of rank-truncated CUR is a sampling-induced oblique tangent projector, so perturbations in its kernel are removed to first order.
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BOOOM: Loss-Function-Agnostic Black-Box Optimization over Orthonormal Manifolds for Machine Learning and Statistical Inference
BOOOM parametrizes Stiefel manifold optimization into Euclidean angle space using global Givens rotations and solves it with recursive modified pattern search for loss-agnostic black-box problems.