Simple non-linear optimizer that solves using non-preconditioned CG. More...

Classes
class	gtsam::NonlinearConjugateGradientOptimizer
	An implementation of the nonlinear CG method using the template below. More...

Namespaces
namespace	gtsam
	Global functions in a separate testing namespace.

Enumerations
enum class	DirectionMethod { FletcherReeves , PolakRibiere , HestenesStiefel , DaiYuan }

Functions
template<typename Gradient>
double	gtsam::FletcherReeves (const Gradient &currentGradient, const Gradient &prevGradient)
	Fletcher-Reeves formula for computing β, the direction of steepest descent.
template<typename Gradient>
double	gtsam::PolakRibiere (const Gradient &currentGradient, const Gradient &prevGradient)
	Polak-Ribiere formula for computing β, the direction of steepest descent.
template<typename Gradient>
double	gtsam::HestenesStiefel (const Gradient &currentGradient, const Gradient &prevGradient, const Gradient &direction)
	The Hestenes-Stiefel formula for computing β, the direction of steepest descent.
template<typename Gradient>
double	gtsam::DaiYuan (const Gradient &currentGradient, const Gradient &prevGradient, const Gradient &direction)
	The Dai-Yuan formula for computing β, the direction of steepest descent.
template<class S, class V, class W>
double	gtsam::lineSearch (const S &system, const V currentValues, const W &gradient)
	Implement the golden-section line search algorithm.
template<class S, class V>
std::tuple< V, int >	gtsam::nonlinearConjugateGradient (const S &system, const V &initial, const NonlinearOptimizerParams &params, const bool singleIteration, const DirectionMethod &directionMethod=DirectionMethod::PolakRibiere, const bool gradientDescent=false)
	Implement the nonlinear conjugate gradient method using the Polak-Ribiere formula suggested in http://en.wikipedia.org/wiki/Nonlinear_conjugate_gradient_method.

Detailed Description

Simple non-linear optimizer that solves using non-preconditioned CG.

Classes