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.
SIAM Journal on Optimization , volume=
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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.