mlpack::optimization Namespace Reference

Namespaces
	test

Classes
class	AdaDelta
	Adadelta is an optimizer that uses two ideas to improve upon the two main drawbacks of the Adagrad method: More...
class	Adam
	Adam is an optimizer that computes individual adaptive learning rates for different parameters from estimates of first and second moments of the gradients. More...
class	AugLagrangian
	The AugLagrangian class implements the Augmented Lagrangian method of optimization. More...
class	AugLagrangianFunction
	This is a utility class used by AugLagrangian, meant to wrap a LagrangianFunction into a function usable by a simple optimizer like L-BFGS. More...
class	AugLagrangianTestFunction
	This function is taken from "Practical Mathematical Optimization" (Snyman), section 5.3.8 ("Application of the Augmented Lagrangian Method"). More...
class	ExponentialSchedule
	The exponential cooling schedule cools the temperature T at every step according to the equation. More...
class	GockenbachFunction
	This function is taken from M. More...
class	GradientDescent
	Gradient Descent is a technique to minimize a function. More...
class	L_BFGS
	The generic L-BFGS optimizer, which uses a back-tracking line search algorithm to minimize a function. More...
class	LovaszThetaSDP
	This function is the Lovasz-Theta semidefinite program, as implemented in the following paper: More...
class	LRSDP
	LRSDP is the implementation of Monteiro and Burer's formulation of low-rank semidefinite programs (LR-SDP). More...
class	LRSDPFunction
	The objective function that LRSDP is trying to optimize. More...
class	MiniBatchSGD
	Mini-batch Stochastic Gradient Descent is a technique for minimizing a function which can be expressed as a sum of other functions. More...
class	PrimalDualSolver
	Interface to a primal dual interior point solver. More...
class	RMSprop
	RMSprop is an optimizer that utilizes the magnitude of recent gradients to normalize the gradients. More...
class	SA
	Simulated Annealing is an stochastic optimization algorithm which is able to deliver near-optimal results quickly without knowing the gradient of the function being optimized. More...
class	SDP
	Specify an SDP in primal form. More...
class	SGD
	Stochastic Gradient Descent is a technique for minimizing a function which can be expressed as a sum of other functions. More...