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

$\underset{x\in {ℝ}^n}{min}f\left(x\right)$

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.

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