ROL
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Provides an interface for the mean plus a sum of arbitrary order variances. More...
#include <ROL_MeanVariance.hpp>
Public Member Functions | |
MeanVariance (const Real order, const Real coeff, const Teuchos::RCP< PositiveFunction< Real > > &pf) | |
Constructor. More... | |
MeanVariance (const std::vector< Real > &order, const std::vector< Real > &coeff, const Teuchos::RCP< PositiveFunction< Real > > &pf) | |
Constructor. More... | |
MeanVariance (Teuchos::ParameterList &parlist) | |
Constructor. More... | |
void | reset (Teuchos::RCP< Vector< Real > > &x0, const Vector< Real > &x) |
Reset internal risk measure storage. Called for value and gradient computation. More... | |
void | reset (Teuchos::RCP< Vector< Real > > &x0, const Vector< Real > &x, Teuchos::RCP< Vector< Real > > &v0, const Vector< Real > &v) |
Reset internal risk measure storage. Called for Hessian-times-a-vector computation. More... | |
void | update (const Real val, const Real weight) |
Update internal risk measure storage for value computation. More... | |
Real | getValue (SampleGenerator< Real > &sampler) |
Return risk measure value. More... | |
void | update (const Real val, const Vector< Real > &g, const Real weight) |
Update internal risk measure storage for gradient computation. More... | |
void | getGradient (Vector< Real > &g, SampleGenerator< Real > &sampler) |
Return risk measure (sub)gradient. More... | |
void | update (const Real val, const Vector< Real > &g, const Real gv, const Vector< Real > &hv, const Real weight) |
Update internal risk measure storage for Hessian-time-a-vector computation. More... | |
void | getHessVec (Vector< Real > &hv, SampleGenerator< Real > &sampler) |
Return risk measure Hessian-times-a-vector. More... | |
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virtual | ~RiskMeasure () |
RiskMeasure (void) | |
Private Types | |
typedef std::vector< Real >::size_type | uint |
Private Member Functions | |
void | checkInputs (void) const |
Private Attributes | |
Teuchos::RCP< PositiveFunction< Real > > | positiveFunction_ |
Teuchos::RCP< Vector< Real > > | dualVector1_ |
Teuchos::RCP< Vector< Real > > | dualVector2_ |
Teuchos::RCP< Vector< Real > > | dualVector3_ |
Teuchos::RCP< Vector< Real > > | dualVector4_ |
std::vector< Real > | order_ |
std::vector< Real > | coeff_ |
uint | NumMoments_ |
std::vector< Real > | weights_ |
std::vector< Real > | value_storage_ |
std::vector< Teuchos::RCP< Vector< Real > > > | gradient_storage_ |
std::vector< Teuchos::RCP< Vector< Real > > > | hessvec_storage_ |
std::vector< Real > | gradvec_storage_ |
bool | firstReset_ |
Additional Inherited Members | |
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Real | val_ |
Real | gv_ |
Teuchos::RCP< Vector< Real > > | g_ |
Teuchos::RCP< Vector< Real > > | hv_ |
Teuchos::RCP< Vector< Real > > | dualVector_ |
bool | firstReset_ |
Provides an interface for the mean plus a sum of arbitrary order variances.
The mean plus variances risk measure is
\[ \mathcal{R}(X) = \mathbb{E}[X] + \sum_{k=1}^n c_k \mathbb{E}[\wp(X-\mathbb{E}[X])^{p_k}] \]
where \(\wp:\mathbb{R}\to[0,\infty)\) is either the absolute value or \((x)_+ = \max\{0,x\}\), \(c_k > 0\) and \(p_k\in\mathbb{N}\). \(\mathcal{R}\) is law-invariant, but not coherent since it violates positive homogeneity. When \(\wp(x) = |x|\), \(\mathcal{R}\) also violates monotonicity.
When using derivative-based optimization, the user can provide a smooth approximation of \((\cdot)_+\) using the ROL::PositiveFunction class.
Definition at line 79 of file ROL_MeanVariance.hpp.
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Definition at line 80 of file ROL_MeanVariance.hpp.
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Constructor.
[in] | order | is the variance order |
[in] | coeff | is the weight for variance term |
[in] | pf | is the plus function or an approximation |
This constructor produces a mean plus variance risk measure with a single variance.
Definition at line 127 of file ROL_MeanVariance.hpp.
References ROL::MeanVariance< Real >::checkInputs(), ROL::MeanVariance< Real >::coeff_, ROL::MeanVariance< Real >::NumMoments_, and ROL::MeanVariance< Real >::order_.
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Constructor.
[in] | order | is a vector of variance orders |
[in] | coeff | is a vector of weights for the variance terms |
[in] | pf | is the plus function or an approximation |
This constructor produces a mean plus variance risk measure with an arbitrary number of variances.
Definition at line 145 of file ROL_MeanVariance.hpp.
References ROL::MeanVariance< Real >::checkInputs(), ROL::MeanVariance< Real >::coeff_, ROL::MeanVariance< Real >::NumMoments_, and ROL::MeanVariance< Real >::order_.
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Constructor.
[in] | parlist | is a parameter list specifying inputs |
parlist should contain sublists "SOL"->"Risk Measure"->"Mean Plus Variance" and within the "Mean Plus Variance" sublist should have the following parameters
Definition at line 171 of file ROL_MeanVariance.hpp.
References ROL::MeanVariance< Real >::checkInputs(), ROL::MeanVariance< Real >::coeff_, ROL::MeanVariance< Real >::NumMoments_, ROL::MeanVariance< Real >::order_, and ROL::MeanVariance< Real >::positiveFunction_.
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Definition at line 102 of file ROL_MeanVariance.hpp.
References ROL::MeanVariance< Real >::coeff_, ROL::MeanVariance< Real >::order_, and ROL::MeanVariance< Real >::positiveFunction_.
Referenced by ROL::MeanVariance< Real >::MeanVariance().
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Reset internal risk measure storage. Called for value and gradient computation.
[out] | x0 | is a user-provided optimization vector |
[in] | x | is a (potentially) augmented risk vector On input, \form#56 carries \form#323 and any statistics (scalars) associated with the risk measure. |
Reimplemented from ROL::RiskMeasure< Real >.
Definition at line 199 of file ROL_MeanVariance.hpp.
References ROL::MeanVariance< Real >::dualVector1_, ROL::MeanVariance< Real >::dualVector2_, ROL::MeanVariance< Real >::dualVector3_, ROL::MeanVariance< Real >::dualVector4_, ROL::MeanVariance< Real >::firstReset_, ROL::MeanVariance< Real >::gradient_storage_, ROL::MeanVariance< Real >::gradvec_storage_, ROL::MeanVariance< Real >::hessvec_storage_, ROL::RiskMeasure< Real >::reset(), ROL::MeanVariance< Real >::value_storage_, and ROL::MeanVariance< Real >::weights_.
Referenced by ROL::MeanVariance< Real >::reset().
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Reset internal risk measure storage. Called for Hessian-times-a-vector computation.
[out] | x0 | is a user-provided optimization vector |
[in] | x | is a (potentially) augmented risk vector |
[out] | v0 | is a user-provided direction vector |
[in] | v | is a (potentially) augmented risk vector On input, \form#56 carries \form#323 and any statistics (scalars) associated with the risk measure. Similarly, \form#37 carries\(v_0\) and any statistics (scalars) associated with the risk measure. |
Reimplemented from ROL::RiskMeasure< Real >.
Definition at line 217 of file ROL_MeanVariance.hpp.
References ROL::RiskVector< Real >::getVector(), and ROL::MeanVariance< Real >::reset().
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Update internal risk measure 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::RiskMeasure< Real >.
Definition at line 224 of file ROL_MeanVariance.hpp.
References ROL::MeanVariance< Real >::value_storage_, and ROL::MeanVariance< Real >::weights_.
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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::RiskMeasure< Real >.
Definition at line 230 of file ROL_MeanVariance.hpp.
References ROL::MeanVariance< Real >::coeff_, ROL::MeanVariance< Real >::NumMoments_, ROL::MeanVariance< Real >::order_, ROL::MeanVariance< Real >::positiveFunction_, ROL::SampleGenerator< Real >::sumAll(), ROL::MeanVariance< Real >::value_storage_, and ROL::MeanVariance< Real >::weights_.
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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::RiskMeasure< Real >.
Definition at line 249 of file ROL_MeanVariance.hpp.
References ROL::Vector< Real >::clone(), ROL::MeanVariance< Real >::gradient_storage_, ROL::MeanVariance< Real >::value_storage_, and ROL::MeanVariance< Real >::weights_.
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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::RiskMeasure< Real >.
Definition at line 260 of file ROL_MeanVariance.hpp.
References ROL::MeanVariance< Real >::coeff_, ROL::MeanVariance< Real >::dualVector1_, ROL::MeanVariance< Real >::dualVector2_, ROL::MeanVariance< Real >::dualVector3_, ROL::MeanVariance< Real >::gradient_storage_, ROL::MeanVariance< Real >::NumMoments_, ROL::MeanVariance< Real >::order_, ROL::MeanVariance< Real >::positiveFunction_, ROL::SampleGenerator< Real >::sumAll(), ROL::MeanVariance< Real >::value_storage_, and ROL::MeanVariance< Real >::weights_.
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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::RiskMeasure< Real >.
Definition at line 286 of file ROL_MeanVariance.hpp.
References ROL::Vector< Real >::clone(), ROL::MeanVariance< Real >::gradient_storage_, ROL::MeanVariance< Real >::gradvec_storage_, ROL::MeanVariance< Real >::hessvec_storage_, ROL::MeanVariance< Real >::value_storage_, and ROL::MeanVariance< Real >::weights_.
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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::RiskMeasure< Real >.
Definition at line 305 of file ROL_MeanVariance.hpp.
References ROL::MeanVariance< Real >::coeff_, ROL::MeanVariance< Real >::dualVector1_, ROL::MeanVariance< Real >::dualVector2_, ROL::MeanVariance< Real >::dualVector3_, ROL::MeanVariance< Real >::dualVector4_, ROL::MeanVariance< Real >::gradient_storage_, ROL::MeanVariance< Real >::gradvec_storage_, ROL::MeanVariance< Real >::hessvec_storage_, ROL::MeanVariance< Real >::NumMoments_, ROL::MeanVariance< Real >::order_, ROL::MeanVariance< Real >::positiveFunction_, ROL::SampleGenerator< Real >::sumAll(), ROL::MeanVariance< Real >::value_storage_, ROL::MeanVariance< Real >::weights_, and ROL::Vector< Real >::zero().
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Definition at line 83 of file ROL_MeanVariance.hpp.
Referenced by ROL::MeanVariance< Real >::checkInputs(), ROL::MeanVariance< Real >::getGradient(), ROL::MeanVariance< Real >::getHessVec(), ROL::MeanVariance< Real >::getValue(), and ROL::MeanVariance< Real >::MeanVariance().
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Definition at line 85 of file ROL_MeanVariance.hpp.
Referenced by ROL::MeanVariance< Real >::getGradient(), ROL::MeanVariance< Real >::getHessVec(), and ROL::MeanVariance< Real >::reset().
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Definition at line 86 of file ROL_MeanVariance.hpp.
Referenced by ROL::MeanVariance< Real >::getGradient(), ROL::MeanVariance< Real >::getHessVec(), and ROL::MeanVariance< Real >::reset().
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Definition at line 87 of file ROL_MeanVariance.hpp.
Referenced by ROL::MeanVariance< Real >::getGradient(), ROL::MeanVariance< Real >::getHessVec(), and ROL::MeanVariance< Real >::reset().
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Definition at line 88 of file ROL_MeanVariance.hpp.
Referenced by ROL::MeanVariance< Real >::getHessVec(), and ROL::MeanVariance< Real >::reset().
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Definition at line 90 of file ROL_MeanVariance.hpp.
Referenced by ROL::MeanVariance< Real >::checkInputs(), ROL::MeanVariance< Real >::getGradient(), ROL::MeanVariance< Real >::getHessVec(), ROL::MeanVariance< Real >::getValue(), and ROL::MeanVariance< Real >::MeanVariance().
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Definition at line 91 of file ROL_MeanVariance.hpp.
Referenced by ROL::MeanVariance< Real >::checkInputs(), ROL::MeanVariance< Real >::getGradient(), ROL::MeanVariance< Real >::getHessVec(), ROL::MeanVariance< Real >::getValue(), and ROL::MeanVariance< Real >::MeanVariance().
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Definition at line 92 of file ROL_MeanVariance.hpp.
Referenced by ROL::MeanVariance< Real >::getGradient(), ROL::MeanVariance< Real >::getHessVec(), ROL::MeanVariance< Real >::getValue(), and ROL::MeanVariance< Real >::MeanVariance().
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Definition at line 94 of file ROL_MeanVariance.hpp.
Referenced by ROL::MeanVariance< Real >::getGradient(), ROL::MeanVariance< Real >::getHessVec(), ROL::MeanVariance< Real >::getValue(), ROL::MeanVariance< Real >::reset(), and ROL::MeanVariance< Real >::update().
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Definition at line 95 of file ROL_MeanVariance.hpp.
Referenced by ROL::MeanVariance< Real >::getGradient(), ROL::MeanVariance< Real >::getHessVec(), ROL::MeanVariance< Real >::getValue(), ROL::MeanVariance< Real >::reset(), and ROL::MeanVariance< Real >::update().
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Definition at line 96 of file ROL_MeanVariance.hpp.
Referenced by ROL::MeanVariance< Real >::getGradient(), ROL::MeanVariance< Real >::getHessVec(), ROL::MeanVariance< Real >::reset(), and ROL::MeanVariance< Real >::update().
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Definition at line 97 of file ROL_MeanVariance.hpp.
Referenced by ROL::MeanVariance< Real >::getHessVec(), ROL::MeanVariance< Real >::reset(), and ROL::MeanVariance< Real >::update().
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Definition at line 98 of file ROL_MeanVariance.hpp.
Referenced by ROL::MeanVariance< Real >::getHessVec(), ROL::MeanVariance< Real >::reset(), and ROL::MeanVariance< Real >::update().
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Definition at line 100 of file ROL_MeanVariance.hpp.
Referenced by ROL::MeanVariance< Real >::reset().