ROL
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Provides an interface for a convex combination of the expected value and the higher moment coherent risk measure. More...
#include <ROL_HMCR.hpp>
Public Member Functions | |
HMCR (const Real prob, const Real lambda, const unsigned order, const ROL::Ptr< PlusFunction< Real > > &pf) | |
Constructor. More... | |
HMCR (ROL::ParameterList &parlist) | |
Constructor. More... | |
void | initialize (const Vector< Real > &x) |
Initialize temporary variables. More... | |
void | updateValue (Objective< Real > &obj, const Vector< Real > &x, const std::vector< Real > &xstat, Real &tol) |
Update internal storage for value computation. More... | |
Real | getValue (const Vector< Real > &x, const std::vector< Real > &xstat, SampleGenerator< Real > &sampler) |
Return risk measure value. More... | |
void | updateGradient (Objective< Real > &obj, const Vector< Real > &x, const std::vector< Real > &xstat, Real &tol) |
Update internal risk measure storage for gradient computation. More... | |
void | getGradient (Vector< Real > &g, std::vector< Real > &gstat, const Vector< Real > &x, const std::vector< Real > &xstat, SampleGenerator< Real > &sampler) |
Return risk measure (sub)gradient. More... | |
void | updateHessVec (Objective< Real > &obj, const Vector< Real > &v, const std::vector< Real > &vstat, const Vector< Real > &x, const std::vector< Real > &xstat, Real &tol) |
Update internal risk measure storage for Hessian-time-a-vector computation. More... | |
void | getHessVec (Vector< Real > &hv, std::vector< Real > &hvstat, const Vector< Real > &v, const std::vector< Real > &vstat, const Vector< Real > &x, const std::vector< Real > &xstat, SampleGenerator< Real > &sampler) |
Return risk measure Hessian-times-a-vector. More... | |
Public Member Functions inherited from ROL::RandVarFunctional< Real > | |
virtual | ~RandVarFunctional () |
RandVarFunctional (void) | |
weight_ (0) | |
void | useStorage (bool storage) |
void | useHessVecStorage (bool storage) |
virtual void | setStorage (const Ptr< ScalarController< Real >> &value_storage, const Ptr< VectorController< Real >> &gradient_storage) |
virtual void | setHessVecStorage (const Ptr< ScalarController< Real >> &gradvec_storage, const Ptr< VectorController< Real >> &hessvec_storage) |
virtual void | resetStorage (bool flag=true) |
Reset internal storage. More... | |
virtual void | resetStorage (UpdateType type) |
virtual void | setSample (const std::vector< Real > &point, const Real weight) |
virtual Real | computeStatistic (const Ptr< const std::vector< Real >> &xstat) const |
Compute statistic. More... | |
Private Member Functions | |
void | checkInputs (void) const |
Private Attributes | |
ROL::Ptr< PlusFunction< Real > > | plusFunction_ |
Real | prob_ |
Real | lambda_ |
unsigned | order_ |
Real | coeff_ |
ROL::Ptr< Vector< Real > > | mDualVector_ |
Real | pnorm_ |
Real | coeff0_ |
Real | coeff1_ |
Real | coeff2_ |
bool | HMCR_firstReset_ |
Additional Inherited Members | |
Protected Member Functions inherited from ROL::RandVarFunctional< Real > | |
Real | computeValue (Objective< Real > &obj, const Vector< Real > &x, Real &tol) |
void | computeGradient (Vector< Real > &g, Objective< Real > &obj, const Vector< Real > &x, Real &tol) |
Real | computeGradVec (Vector< Real > &g, Objective< Real > &obj, const Vector< Real > &v, const Vector< Real > &x, Real &tol) |
void | computeHessVec (Vector< Real > &hv, Objective< Real > &obj, const Vector< Real > &v, const Vector< Real > &x, Real &tol) |
Protected Attributes inherited from ROL::RandVarFunctional< Real > | |
Real | val_ |
Real | gv_ |
Ptr< Vector< Real > > | g_ |
Ptr< Vector< Real > > | hv_ |
Ptr< Vector< Real > > | dualVector_ |
bool | firstReset_ |
std::vector< Real > | point_ |
Real | weight_ |
Provides an interface for a convex combination of the expected value and the higher moment coherent risk measure.
The higher moment coherent risk measure of order \(p\) with confidence level \(0\le \beta < 1\) is
\[ \mathcal{R}(X) = \inf_{t\in\mathbb{R}} \left\{ t + \frac{1}{1-\beta} \mathbb{E}\left[(X-t)_+^p\right]^{1/p} \right\} \]
where \((x)_+ = \max\{0,x\}\). \(\mathcal{R}\) is a law-invariant coherent risk measure. ROL implements this by augmenting the optimization vector \(x_0\) with the parameter \(t\), then minimizes jointly for \((x_0,t)\).
The user can provide a smooth approximation of \((\cdot)_+\) using the ROL::PlusFunction class.
Definition at line 41 of file ROL_HMCR.hpp.
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Constructor.
[in] | prob | is the confidence level |
[in] | lambda | is the convex combination parameter (lambda=0 corresponds to the expected value whereas lambda=1 corresponds to the higher moment coherent risk measure) |
[in] | order | is the order of higher moment coherent risk measure |
[in] | pf | is the plus function or an approximation |
Definition at line 100 of file ROL_HMCR.hpp.
References ROL::HMCR< Real >::checkInputs(), ROL::HMCR< Real >::coeff_, and ROL::HMCR< Real >::prob_.
Constructor.
[in] | parlist | is a parameter list specifying inputs |
parlist should contain sublists "SOL"->"Risk Measure"->"HMCR" and within the "HMCR" sublist should have the following parameters
Definition at line 122 of file ROL_HMCR.hpp.
References ROL::HMCR< Real >::checkInputs(), ROL::HMCR< Real >::coeff_, ROL::HMCR< Real >::lambda_, ROL::HMCR< Real >::order_, ROL::HMCR< Real >::plusFunction_, and ROL::HMCR< Real >::prob_.
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Definition at line 78 of file ROL_HMCR.hpp.
References ROL::HMCR< Real >::lambda_, ROL::HMCR< Real >::order_, ROL::HMCR< Real >::plusFunction_, ROL::HMCR< Real >::prob_, and zero.
Referenced by ROL::HMCR< Real >::HMCR().
Initialize temporary variables.
[in] | x | is a vector used for initializing storage |
Reimplemented from ROL::RandVarFunctional< Real >.
Definition at line 140 of file ROL_HMCR.hpp.
References ROL::HMCR< Real >::coeff0_, ROL::HMCR< Real >::coeff1_, ROL::HMCR< Real >::coeff2_, ROL::Vector< Real >::dual(), ROL::HMCR< Real >::HMCR_firstReset_, ROL::RandVarFunctional< Real >::initialize(), ROL::HMCR< Real >::mDualVector_, ROL::HMCR< Real >::pnorm_, and zero.
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Update internal storage for value computation.
[in] | val | is the value of the random variable objective function at the current sample point |
[in] | weight | is the weight associated with the current sample point |
Reimplemented from ROL::RandVarFunctional< Real >.
Definition at line 154 of file ROL_HMCR.hpp.
References ROL::RandVarFunctional< Real >::computeValue(), ROL::HMCR< Real >::order_, ROL::HMCR< Real >::plusFunction_, ROL::HMCR< Real >::pnorm_, ROL::RandVarFunctional< Real >::val_, and ROL::RandVarFunctional< Real >::weight_.
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Return risk measure value.
[in] | sampler | is the ROL::SampleGenerator used to sample the objective function |
Upon return, getValue returns \(\mathcal{R}(f(x_0))\) where \(f(x_0)\) denotes the random variable objective function evaluated at \(x_0\).
Reimplemented from ROL::RandVarFunctional< Real >.
Definition at line 167 of file ROL_HMCR.hpp.
References ROL::HMCR< Real >::coeff_, ROL::HMCR< Real >::lambda_, ROL::HMCR< Real >::order_, ROL::HMCR< Real >::pnorm_, ROL::SampleGenerator< Real >::sumAll(), and ROL::RandVarFunctional< Real >::val_.
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Update internal risk measure storage for gradient computation.
[in] | val | is the value of the random variable objective function at the current sample point |
[in] | g | is the gradient of the random variable objective function at the current sample point |
[in] | weight | is the weight associated with the current sample point |
Reimplemented from ROL::RandVarFunctional< Real >.
Definition at line 180 of file ROL_HMCR.hpp.
References ROL::HMCR< Real >::coeff0_, ROL::RandVarFunctional< Real >::computeGradient(), ROL::RandVarFunctional< Real >::computeValue(), ROL::RandVarFunctional< Real >::dualVector_, ROL::RandVarFunctional< Real >::g_, ROL::RandVarFunctional< Real >::hv_, ROL::HMCR< Real >::order_, ROL::HMCR< Real >::plusFunction_, ROL::HMCR< Real >::pnorm_, and ROL::RandVarFunctional< Real >::weight_.
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Return risk measure (sub)gradient.
[out] | g | is the (sub)gradient of the risk measure |
[in] | sampler | is the ROL::SampleGenerator used to sample the objective function |
Upon return, getGradient returns \(\theta\in\partial\mathcal{R}(f(x_0))\) where \(f(x_0)\) denotes the random variable objective function evaluated at \(x_0\) and \(\partial\mathcal{R}(X)\) denotes the subdifferential of \(\mathcal{R}\) at \(X\).
Reimplemented from ROL::RandVarFunctional< Real >.
Definition at line 204 of file ROL_HMCR.hpp.
References ROL::Vector< Real >::axpy(), ROL::HMCR< Real >::coeff0_, ROL::HMCR< Real >::coeff_, ROL::RandVarFunctional< Real >::dualVector_, ROL::RandVarFunctional< Real >::g_, ROL::RandVarFunctional< Real >::hv_, ROL::HMCR< Real >::lambda_, ROL::HMCR< Real >::order_, ROL::HMCR< Real >::pnorm_, ROL::Vector< Real >::scale(), ROL::SampleGenerator< Real >::sumAll(), and zero.
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Update internal risk measure storage for Hessian-time-a-vector computation.
[in] | val | is the value of the random variable objective function at the current sample point |
[in] | g | is the gradient of the random variable objective function at the current sample point |
[in] | gv | is the gradient of the random variable objective function at the current sample point applied to the vector v0 |
[in] | hv | is the Hessian of the random variable objective function at the current sample point applied to the vector v0 |
[in] | weight | is the weight associated with the current sample point |
Reimplemented from ROL::RandVarFunctional< Real >.
Definition at line 232 of file ROL_HMCR.hpp.
References ROL::HMCR< Real >::coeff0_, ROL::HMCR< Real >::coeff1_, ROL::HMCR< Real >::coeff2_, ROL::RandVarFunctional< Real >::computeGradVec(), ROL::RandVarFunctional< Real >::computeHessVec(), ROL::RandVarFunctional< Real >::computeValue(), ROL::RandVarFunctional< Real >::dualVector_, ROL::RandVarFunctional< Real >::g_, ROL::RandVarFunctional< Real >::hv_, ROL::HMCR< Real >::mDualVector_, ROL::HMCR< Real >::order_, ROL::HMCR< Real >::plusFunction_, ROL::HMCR< Real >::pnorm_, and ROL::RandVarFunctional< Real >::weight_.
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Return risk measure Hessian-times-a-vector.
[out] | hv | is the Hessian-times-a-vector of the risk measure |
[in] | sampler | is the ROL::SampleGenerator used to sample the objective function |
Upon return, getHessVec returns \(\nabla^2 \mathcal{R}(f(x_0))v_0\) (if available) where \(f(x_0)\) denotes the random variable objective function evaluated at \(x_0\).
Reimplemented from ROL::RandVarFunctional< Real >.
Definition at line 270 of file ROL_HMCR.hpp.
References ROL::Vector< Real >::axpy(), ROL::HMCR< Real >::coeff0_, ROL::HMCR< Real >::coeff1_, ROL::HMCR< Real >::coeff2_, ROL::HMCR< Real >::coeff_, ROL::RandVarFunctional< Real >::dualVector_, ROL::RandVarFunctional< Real >::g_, ROL::RandVarFunctional< Real >::hv_, ROL::HMCR< Real >::lambda_, ROL::HMCR< Real >::mDualVector_, ROL::HMCR< Real >::order_, ROL::HMCR< Real >::pnorm_, ROL::Vector< Real >::scale(), ROL::SampleGenerator< Real >::sumAll(), and zero.
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Definition at line 44 of file ROL_HMCR.hpp.
Referenced by ROL::HMCR< Real >::checkInputs(), ROL::HMCR< Real >::HMCR(), ROL::HMCR< Real >::updateGradient(), ROL::HMCR< Real >::updateHessVec(), and ROL::HMCR< Real >::updateValue().
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Definition at line 45 of file ROL_HMCR.hpp.
Referenced by ROL::HMCR< Real >::checkInputs(), and ROL::HMCR< Real >::HMCR().
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Definition at line 46 of file ROL_HMCR.hpp.
Referenced by ROL::HMCR< Real >::checkInputs(), ROL::HMCR< Real >::getGradient(), ROL::HMCR< Real >::getHessVec(), ROL::HMCR< Real >::getValue(), and ROL::HMCR< Real >::HMCR().
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Definition at line 47 of file ROL_HMCR.hpp.
Referenced by ROL::HMCR< Real >::checkInputs(), ROL::HMCR< Real >::getGradient(), ROL::HMCR< Real >::getHessVec(), ROL::HMCR< Real >::getValue(), ROL::HMCR< Real >::HMCR(), ROL::HMCR< Real >::updateGradient(), ROL::HMCR< Real >::updateHessVec(), and ROL::HMCR< Real >::updateValue().
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Definition at line 50 of file ROL_HMCR.hpp.
Referenced by ROL::HMCR< Real >::getGradient(), ROL::HMCR< Real >::getHessVec(), ROL::HMCR< Real >::getValue(), and ROL::HMCR< Real >::HMCR().
Definition at line 53 of file ROL_HMCR.hpp.
Referenced by ROL::HMCR< Real >::getHessVec(), ROL::HMCR< Real >::initialize(), and ROL::HMCR< Real >::updateHessVec().
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Definition at line 56 of file ROL_HMCR.hpp.
Referenced by ROL::HMCR< Real >::getGradient(), ROL::HMCR< Real >::getHessVec(), ROL::HMCR< Real >::getValue(), ROL::HMCR< Real >::initialize(), ROL::HMCR< Real >::updateGradient(), ROL::HMCR< Real >::updateHessVec(), and ROL::HMCR< Real >::updateValue().
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Definition at line 57 of file ROL_HMCR.hpp.
Referenced by ROL::HMCR< Real >::getGradient(), ROL::HMCR< Real >::getHessVec(), ROL::HMCR< Real >::initialize(), ROL::HMCR< Real >::updateGradient(), and ROL::HMCR< Real >::updateHessVec().
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Definition at line 58 of file ROL_HMCR.hpp.
Referenced by ROL::HMCR< Real >::getHessVec(), ROL::HMCR< Real >::initialize(), and ROL::HMCR< Real >::updateHessVec().
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Definition at line 59 of file ROL_HMCR.hpp.
Referenced by ROL::HMCR< Real >::getHessVec(), ROL::HMCR< Real >::initialize(), and ROL::HMCR< Real >::updateHessVec().
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Definition at line 62 of file ROL_HMCR.hpp.
Referenced by ROL::HMCR< Real >::initialize().