In the unconstrained minimization problem, the Wolfe conditions (also known as the Armijo-Wolfe conditions in some books) are a set of inequalities for performing inexact line search, especially in quasi-Newton methods, first published by Philip Wolfe in 1969 (also named after Larry Armijo). In these methods the idea is to find min x f ( x ) {\displaystyle \min _{x}f(\mathbf {x} )} for some smooth f : R n → R {\displaystyle f\colon \mathbb {R} ^{n}\to \mathbb {R} } .
In the unconstrained minimization problem, the Wolfe conditions (also known as the Armijo-Wolfe conditions in some books) are a set of inequalities for performing inexact line search, especially in quasi-Newton methods, first published by Philip Wolfe in 1969 (also named after Larry Armijo). In these methods the idea is to find min x f ( x ) {\displaystyle \min _{x}f(\mathbf {x} )} for some smooth f : R n → R {\displaystyle f\colon \mathbb {R} ^{n}\to \mathbb {R} } .
Source: Wikipedia "Wolfe conditions" · CC BY-SA 4.0
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