|LineMinimizer<EvaluatorType extends Evaluator<java.lang.Double,java.lang.Double>>||
Defines the functionality of a line-minimization algorithm, often called a "line search" algorithm.
|AbstractAnytimeLineMinimizer<EvaluatorType extends Evaluator<java.lang.Double,java.lang.Double>>||
Partial AnytimeAlgorithm implementation of a LineMinimizer.
Creates a truly differentiable scalar function from a differentiable Vector function, instead of using a forward-differences approximation to the derivative like DirectionalVectorToScalarFunction does.
Maps a vector function onto a scalar one by using a directional vector and vector offset, and the parameter to the function is a scalar value along the direction from the start-point offset.
Stores an InputOutputPair with corresponding slope (gradient) information
Class that defines a bracket for a scalar function.
Implementation of the backtracking line-minimization algorithm.
This is an implementation of a line-minimization algorithm proposed by Fletcher that makes extensive use of first-order derivative information.
This is an implementation of a LineMinimizer that does not require derivative information.
The Wolfe conditions define a set of sufficient conditions for "sufficient decrease" in inexact line search.