Newton-Schulz

A numerical method that iteratively approximates the inverse square root of a matrix through matrix polynomial iteration. It is commonly used in optimizers as a substitute for singular value decomposition to achieve efficient orthogonalization. The iteration avoids the computational cost of decomposition-based approaches while producing an approximation of the required matrix function.