#include <shark/Data/Pgm.h>#include <shark/Data/Csv.h>#include <shark/Data/Statistics.h>#include <shark/ObjectiveFunctions/SparseAutoencoderError.h>#include <shark/Algorithms/GradientDescent/LBFGS.h>#include <shark/ObjectiveFunctions/Loss/SquaredLoss.h>#include <shark/ObjectiveFunctions/Regularizer.h>#include <shark/Core/Timer.h>Go to the source code of this file.
Functions | |
| UnlabeledData< RealVector > | getSamples () |
| void | initializeFFNet (Autoencoder< LogisticNeuron, LogisticNeuron > &model) |
| int | main () |
Variables | |
| const unsigned int | numsamples = 10000 |
| const std::size_t | w = 512 |
| const std::size_t | h = 512 |
| const std::size_t | psize = 8 |
| const unsigned int | numhidden = 25 |
| const double | rho = 0.01 |
| const double | beta = 6.0 |
| const double | lambda = 0.0002 |
| const unsigned int | maxIter = 400 |
| UnlabeledData<RealVector> getSamples | ( | ) |
Definition at line 30 of file SparseAETutorial.cpp.
References shark::createDataFromRange(), shark::random::discrete(), shark::Data< Type >::elements(), shark::random::globalRng, h, shark::importCSV(), shark::mean(), shark::Data< Type >::numberOfElements(), numsamples, psize, shark::transform(), shark::variance(), and w.
Referenced by main().
| void initializeFFNet | ( | Autoencoder< LogisticNeuron, LogisticNeuron > & | model | ) |
Definition at line 79 of file SparseAETutorial.cpp.
References shark::random::globalRng, and shark::random::uni().
Referenced by main().
| int main | ( | ) |
Definition at line 93 of file SparseAETutorial.cpp.
References beta, shark::exportFiltersToPGMGrid(), getSamples(), shark::random::globalRng, shark::AbstractLineSearchOptimizer::init(), initializeFFNet(), lambda, maxIter, shark::Data< Type >::numberOfElements(), numhidden, psize, rho, shark::AbstractSingleObjectiveOptimizer< PointType >::solution(), shark::AbstractLineSearchOptimizer::step(), shark::Timer::stop(), and shark::ResultSet< SearchPointT, ResultT >::value.
| const double beta = 6.0 |
Definition at line 24 of file SparseAETutorial.cpp.
Referenced by shark::annealedImportanceSampling(), shark::blas::applyHouseholderOnTheLeft(), shark::blas::applyHouseholderOnTheRight(), shark::estimateLogFreeEnergy(), shark::GaussianLayer::logMarginalize(), shark::logPartitionFunction(), main(), shark::negativeLogLikelihood(), shark::CMAChromosome::serialize(), and shark::RegularizationNetworkTrainer< InputType >::setPrecision().
| const std::size_t h = 512 |
Definition at line 18 of file SparseAETutorial.cpp.
Referenced by shark::QpMcBoxDecomp< Matrix >::deactivateVariable(), shark::QpMcSimplexDecomp< Matrix >::deactivateVariable(), shark::DTLZ7::eval(), shark::MergeBudgetMaintenanceStrategy< RealVector >::MergingProblemFunction::eval(), shark::MergeBudgetMaintenanceStrategy< RealVector >::MergingProblemFunction::evalDerivative(), getSamples(), and shark::MergeBudgetMaintenanceStrategy< RealVector >::reduceBudget().
| const double lambda = 0.0002 |
Definition at line 25 of file SparseAETutorial.cpp.
Referenced by shark::LMCMA::init(), main(), shark::LinearSAGTrainer< InputType, LabelType >::setLambda(), shark::LogisticRegression< InputVectorType >::setLambda1(), shark::LogisticRegression< InputVectorType >::setLambda2(), shark::Pegasos< VectorType >::solve(), shark::McPegasos< VectorType >::solve(), shark::LMCMA::step(), shark::LMCMA::suggestLambda(), shark::KernelSGDTrainer< InputType, CacheType >::train(), shark::KernelBudgetedSGDTrainer< InputType, CacheType >::train(), shark::random::truncExp(), and shark::PopulationBasedStepSizeAdaptation::update().
| const unsigned int maxIter = 400 |
Definition at line 28 of file SparseAETutorial.cpp.
Referenced by main().
| const unsigned int numhidden = 25 |
Definition at line 22 of file SparseAETutorial.cpp.
Referenced by main().
| const unsigned int numsamples = 10000 |
Definition at line 16 of file SparseAETutorial.cpp.
Referenced by getSamples().
| const std::size_t psize = 8 |
Definition at line 19 of file SparseAETutorial.cpp.
Referenced by getSamples(), and main().
| const double rho = 0.01 |
Definition at line 23 of file SparseAETutorial.cpp.
Referenced by main().
| const std::size_t w = 512 |
Definition at line 17 of file SparseAETutorial.cpp.
Referenced by getSamples(), shark::ReferenceVectorAdaptation< shark::Individual >::operator()(), shark::WeightedSumKernel< InputType >::setParameterVector(), shark::Pegasos< VectorType >::solve(), shark::QpMcLinear< InputT >::solve(), shark::tchebycheffScalarizer(), shark::LassoRegression< InputVectorType >::train(), shark::LinearCSvmTrainer< InputType >::train(), shark::SquaredHingeLinearCSvmTrainer< InputType >::train(), shark::QpMcSimplexDecomp< Matrix >::updateSMO(), and shark::QpMcBoxDecomp< Matrix >::updateSMO().