= Broyden–Fletcher–Goldfarb–Shanno algorithm
{wiki=Broyden–Fletcher–Goldfarb–Shanno_algorithm}
The Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm is an iterative method for solving unconstrained nonlinear optimization problems. It is part of a broader class of algorithms known as quasi-Newton methods, which are used to find local minima of differentiable functions. The key idea behind quasi-Newton methods is to use an approximation to the Hessian matrix (the matrix of second derivatives of the objective function) to facilitate efficient optimization.
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