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.
Journal of the ACM , volume=
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
math.OC 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
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.