Efficient Optimization on the Euclidean Sphere: Riemannian Gradient Alignment as a Unifying Principle

Euclidean sphere-constrained optimization problems represent perhaps the most basic class of nonconvex-constrained problems for which there exist efficient optimization algorithms for specific problem instances, such as the eigenvalue problems and learning problems arising in the recent literature.