- gradient minimization method
- Макаров: метод градиентной минимизации
Универсальный англо-русский словарь. Академик.ру. 2011.
Универсальный англо-русский словарь. Академик.ру. 2011.
Energy minimization — (energy optimization) methods are common techniques to compute the equilibrium configuration of molecules. The basic idea is that a stable state of a molecular system should correspond to a local minimum of their potential energy. This kind of… … Wikipedia
Conjugate gradient method — A comparison of the convergence of gradient descent with optimal step size (in green) and conjugate vector (in red) for minimizing a quadratic function associated with a given linear system. Conjugate gradient, assuming exact arithmetic,… … Wikipedia
Nelder–Mead method — Nelder–Mead simplex search over the Rosenbrock banana function (above) and Himmelblau s function (below) See simplex algorithm for Dantzig s algorithm for the problem of linear opti … Wikipedia
Newton's method — In numerical analysis, Newton s method (also known as the Newton–Raphson method), named after Isaac Newton and Joseph Raphson, is a method for finding successively better approximations to the roots (or zeroes) of a real valued function. The… … Wikipedia
Newton's method in optimization — A comparison of gradient descent (green) and Newton s method (red) for minimizing a function (with small step sizes). Newton s method uses curvature information to take a more direct route. In mathematics, Newton s method is an iterative method… … Wikipedia
BFGS method — In mathematics, the Broyden Fletcher Goldfarb Shanno (BFGS) method is a method to solve an unconstrained nonlinear optimization problem. The BFGS method is derived from the Newton s method in optimization, a class of hill climbing optimization… … Wikipedia
Cutting-plane method — In mathematical optimization, the cutting plane method is an umbrella term for optimization methods which iteratively refine a feasible set or objective function by means of linear inequalities, termed cuts. Such procedures are popularly used to… … Wikipedia
Nonlinear conjugate gradient method — In numerical optimization, the nonlinear conjugate gradient method generalizes the conjugate gradient method to nonlinear optimization. For a quadratic function : The minimum of f is obtained when the gradient is 0: . Whereas linear conjugate… … Wikipedia
Derivation of the conjugate gradient method — In numerical linear algebra, the conjugate gradient method is an iterative method for numerically solving the linear system where is symmetric positive definite. The conjugate gradient method can be derived from several different perspectives,… … Wikipedia
Iterative method — In computational mathematics, an iterative method is a mathematical procedure that generates a sequence of improving approximate solutions for a class of problems. A specific implementation of an iterative method, including the termination… … Wikipedia
Quasi-Newton method — In optimization, quasi Newton methods (also known as variable metric methods) are well known algorithms for finding local maxima and minima of functions. Quasi Newton methods are based on Newton s method to find the stationary point of a function … Wikipedia