Gradient method
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Names in other languages
- РусскийГрадиентные методы
- УкраїнськаГрадієнтні методи
- EnglishGradient method
- 中文梯度方法
- 日本語勾配法
Article bodies are English and are not machine-translated. A name in another language is not a translation of the article.
In optimization, a gradient method is an algorithm to solve problems of the form : \min_{x\in\mathbb R^n}\; f(x) with the search directions defined by the gradient of the function at the current point. Examples of gradient methods are the gradient descent and the conjugate gradient.
In optimization, a gradient method is an algorithm to solve problems of the form \min_{x\in\mathbb R^n}\; f(x) with the search directions defined by the gradient of the function at the current point. Examples of gradient methods are the gradient descent and the conjugate gradient. ==See also== Gradient descent Stochastic gradient descent Coordinate descent Frank–Wolfe algorithm Landweber iteration Random coordinate descent Conjugate gradient method Derivation of the conjugate gradient method Nonlinear conjugate gradient method Biconjugate gradient method Biconjugate gradient stabilized method ==References==
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