# Wolfe Conditions

In the unconstrained minimization problem, the Wolfe conditions are a set of inequalities for performing inexact line search, especially in quasi-Newton methods.

In these methods the idea is to find

for some smooth . Each step often involves approximately solving the subproblem

where is the current best guess, is a search direction, and is the step length.

Then inexact line searches provide an efficient way of computing an acceptable step length that reduces the objective function 'sufficiently', rather than minimizing the objective function over exactly. A line search algorithm can use Wolfe conditions as a requirement for any guessed, before finding a new search direction .

### Other articles related to "wolfe conditions, condition":

Wolfe Conditions - Strong Wolfe Condition On Curvature
... The Wolfe conditions, however, can result in a value for the step length that is not close to a minimizer of ... If we modify the curvature condition to the following, iia) then i) and iia) together form the so-called strong Wolfe conditions, and force to lie close to a critical point of ... The principal reason for imposing the Wolfe conditions in an optimization algorithm where is to ensure convergence of the gradient to zero ...

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