The generic L-BFGS optimizer, which uses a back-tracking line search algorithm to minimize a function.
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| | L_BFGS (FunctionType &function, const size_t numBasis=10, const size_t maxIterations=10000, const double armijoConstant=1e-4, const double wolfe=0.9, const double minGradientNorm=1e-6, const double factr=1e-15, const size_t maxLineSearchTrials=50, const double minStep=1e-20, const double maxStep=1e20) |
| | Initialize the L-BFGS object. More...
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| double | ArmijoConstant () const |
| | Get the Armijo condition constant. More...
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| double & | ArmijoConstant () |
| | Modify the Armijo condition constant. More...
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| double | Factr () const |
| | Get the factr value. More...
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| double & | Factr () |
| | Modify the factr value. More...
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| const FunctionType & | Function () const |
| | Return the function that is being optimized. More...
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| FunctionType & | Function () |
| | Modify the function that is being optimized. More...
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| size_t | MaxIterations () const |
| | Get the maximum number of iterations. More...
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| size_t & | MaxIterations () |
| | Modify the maximum number of iterations. More...
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| size_t | MaxLineSearchTrials () const |
| | Get the maximum number of line search trials. More...
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| size_t & | MaxLineSearchTrials () |
| | Modify the maximum number of line search trials. More...
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| double | MaxStep () const |
| | Return the maximum line search step size. More...
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| double & | MaxStep () |
| | Modify the maximum line search step size. More...
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| double | MinGradientNorm () const |
| | Get the minimum gradient norm. More...
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| double & | MinGradientNorm () |
| | Modify the minimum gradient norm. More...
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| const std::pair< arma::mat, double > & | MinPointIterate () const |
| | Return the point where the lowest function value has been found. More...
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| double | MinStep () const |
| | Return the minimum line search step size. More...
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| double & | MinStep () |
| | Modify the minimum line search step size. More...
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| size_t | NumBasis () const |
| | Get the memory size. More...
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| size_t & | NumBasis () |
| | Modify the memory size. More...
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| double | Optimize (arma::mat &iterate) |
| | Use L-BFGS to optimize the given function, starting at the given iterate point and finding the minimum. More...
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| double | Optimize (arma::mat &iterate, const size_t maxIterations) |
| | Use L-BFGS to optimize (minimize) the given function, starting at the given iterate point, and performing no more than the given maximum number of iterations (the class variable maxIterations is ignored for this run, but not modified). More...
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| double | Wolfe () const |
| | Get the Wolfe parameter. More...
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| double & | Wolfe () |
| | Modify the Wolfe parameter. More...
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| double | ChooseScalingFactor (const size_t iterationNum, const arma::mat &gradient) |
| | Calculate the scaling factor, gamma, which is used to scale the Hessian approximation matrix. More...
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| double | Evaluate (const arma::mat &iterate) |
| | Evaluate the function at the given iterate point and store the result if it is a new minimum. More...
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| bool | GradientNormTooSmall (const arma::mat &gradient) |
| | Check to make sure that the norm of the gradient is not smaller than 1e-5. More...
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| bool | LineSearch (double &functionValue, arma::mat &iterate, arma::mat &gradient, const arma::mat &searchDirection) |
| | Perform a back-tracking line search along the search direction to calculate a step size satisfying the Wolfe conditions. More...
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| void | SearchDirection (const arma::mat &gradient, const size_t iterationNum, const double scalingFactor, arma::mat &searchDirection) |
| | Find the L-BFGS search direction. More...
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| void | UpdateBasisSet (const size_t iterationNum, const arma::mat &iterate, const arma::mat &oldIterate, const arma::mat &gradient, const arma::mat &oldGradient) |
| | Update the y and s matrices, which store the differences between the iterate and old iterate and the differences between the gradient and the old gradient, respectively. More...
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template<typename FunctionType>
class mlpack::optimization::L_BFGS< FunctionType >
The generic L-BFGS optimizer, which uses a back-tracking line search algorithm to minimize a function.
The parameters for the algorithm (number of memory points, maximum step size, and so forth) are all configurable via either the constructor or standalone modifier functions. A function which can be optimized by this class must implement the following methods:
Definition at line 34 of file lbfgs.hpp.
template<typename FunctionType>
Use L-BFGS to optimize the given function, starting at the given iterate point and finding the minimum.
The maximum number of iterations is set in the constructor (or with MaxIterations()). Alternately, another overload is provided which takes a maximum number of iterations as a parameter. The given starting point will be modified to store the finishing point of the algorithm, and the final objective value is returned.
- Parameters
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| iterate | Starting point (will be modified). |
- Returns
- Objective value of the final point.
template<typename FunctionType>
Use L-BFGS to optimize (minimize) the given function, starting at the given iterate point, and performing no more than the given maximum number of iterations (the class variable maxIterations is ignored for this run, but not modified).
The given starting point will be modified to store the finishing point of the algorithm, and the final objective value is returned.
- Parameters
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| iterate | Starting point (will be modified). |
| maxIterations | Maximum number of iterations (0 specifies no limit). |
- Returns
- Objective value of the final point.
1.8.11
