Gradient method

In optimization, a gradient method is an algorithm to solve problems of the form

${\displaystyle \min _{x\in \mathbb {R} ^{n}}\;f(x)}${\displaystyle \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.

• Elijah Polak (1997). Optimization : Algorithms and Consistent Approximations. Springer-Verlag. ISBN 0-387-94971-2.

• First order methods
• Optimization algorithms and methods
• Numerical linear algebra
• Gradient methods
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