#include <GradientDescent.hpp>
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typedef ParameterType::Scalar | Scalar |
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typedef ParameterType::Scalar | Scalar |
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| ConstantLineSearch (Scalar alpha) |
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Scalar | search (const ProblemType &problem, Eigen::Ref< ParameterType > x0, const ParameterType &grad_x0, const ParameterType &direction) |
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template<typename ProblemType, typename ParameterType>
class ldaplusplus::optimization::ConstantLineSearch< ProblemType, ParameterType >
ConstantLineSearch simply updates the parameter by a costant factor of the direction performing no line search actually.
template<typename ProblemType , typename ParameterType >
- Parameters
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alpha | The amount to move towards the search direction |
template<typename ProblemType , typename ParameterType >
Search for a good enough function value in the direction given and the function given.
This function changes its parameter x0 which is passed by reference.
- Parameters
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problem | The function to be minimized |
x0 | The improved position (passed by reference) |
grad_x0 | The gradient at the initial x0 |
direction | The direction of search which can be different than the gradient to account for Newton methods |
- Returns
- The function value at the final x0
Implements ldaplusplus::optimization::LineSearch< ProblemType, ParameterType >.
The documentation for this class was generated from the following file: