#include <alpaqa/accelerators/steihaugcg.hpp>
template<Config Conf>
struct alpaqa::SteihaugCG< Conf >
Steihaug conjugate gradients procedure based on https://github.com/scipy/scipy/blob/583e70a50573169fc352b5dc6d94588a97c7389a/scipy/optimize/_trustregion_ncg.py#L44.
Definition at line 39 of file steihaugcg.hpp.
◆ Params
◆ SteihaugCG() [1/2]
◆ SteihaugCG() [2/2]
◆ resize()
◆ solve()
template<Config Conf>
template<class HessFun>
real_t solve |
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const auto & | grad, |
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const HessFun & | hess_prod, |
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real_t | trust_radius, |
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rvec | step ) const |
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inline |
◆ get_boundaries_intersections()
Solve the scalar quadratic equation ||z + t d|| == trust_radius.
This is like a line-sphere intersection. Return the two values of t, sorted from low to high.
Definition at line 146 of file steihaugcg.hpp.
◆ params
◆ Bd
◆ work_eval
The documentation for this struct was generated from the following file: