square-rooting a matrix so a whole system of equations gets cheaper to solve.
means a way to break a symmetric positive-definite matrix A into L times L-transpose, where L is lower triangular, so solving Ax=b becomes two easy triangular solves instead of one hard one.
from named after andre-louis cholesky, a french military engineer who developed the method for geodesic surveying and artillery calculations before world war one, and never published it himself; a colleague released it posthumously in 1924 after cholesky died in combat in 1918.
kalman filters — used to factor covariance matrices at every update step
monte carlo simulation — generates correlated random variables in quant finance models
gaussian process regression — factors the kernel matrix to invert it cheaply
structural engineering fea — solves stiffness matrix systems in finite element analysis