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gradient search

См. также в других словарях:

  • Gradient descent — For the analytical method called steepest descent see Method of steepest descent. Gradient descent is an optimization algorithm. To find a local minimum of a function using gradient descent, one takes steps proportional to the negative of the… …   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

  • 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

  • Cuckoo search — (CS) is an optimization algorithm developed by Xin she Yang and Suash Deb in 2009.[1][2] It was inspired by the obligate brood parasitism of some cuckoo species by laying their eggs in the nests of other host birds (of other species). Some host… …   Wikipedia

  • Harmony search — (HS) is a metaheuristic algorithm (also known as soft computing algorithm or evolutionary algorithm) mimicking the improvisation process of musicians. In the process, each musician plays a note for finding a best harmony all together. Likewise,… …   Wikipedia

  • Stochastic gradient descent — is a general optimization algorithm, but is typically used to fit the parameters of a machine learning model.In standard (or batch ) gradient descent, the true gradient is used to update the parameters of the model. The true gradient is usually… …   Wikipedia

  • Line search — In (unconstrained) optimization, the line search strategy is one of two basic iterative approaches to finding a local minimum mathbf{x}^* of an objective function f:mathbb R^n omathbb R. The other method is that of trust regions.… …   Wikipedia

  • Non-linear least squares — is the form of least squares analysis which is used to fit a set of m observations with a model that is non linear in n unknown parameters (m > n). It is used in some forms of non linear regression. The basis of the method is to… …   Wikipedia

  • Natural evolution strategy — Natural evolution strategies (NES) are a family of numerical optimization algorithms for black box problems. Similar in spirit to evolution strategies, they iteratively update the (continuous) parameters of a search distribution by following the… …   Wikipedia

  • Wind — For other uses, see Wind (disambiguation). Wind, from the …   Wikipedia

  • CMA-ES — stands for Covariance Matrix Adaptation Evolution Strategy. Evolution strategies (ES) are stochastic, derivative free methods for numerical optimization of non linear or non convex continuous optimization problems. They belong to the class of… …   Wikipedia

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