katyusha.hpp

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#ifndef MLPACK_CORE_OPTIMIZERS_KATYUSHA_KATYUSHA_HPP
#define MLPACK_CORE_OPTIMIZERS_KATYUSHA_KATYUSHA_HPP

#include <mlpack/prereqs.hpp>

namespace mlpack {
namespace optimization {

template<bool Proximal = false>
class KatyushaType
{
 public:
  KatyushaType(const double convexity = 1.0,
               const double lipschitz = 10.0,
               const size_t batchSize = 32,
               const size_t maxIterations = 1000,
               const size_t innerIterations = 0,
               const double tolerance = 1e-5,
               const bool shuffle = true);

  template<typename DecomposableFunctionType>
  double Optimize(DecomposableFunctionType& function, arma::mat& iterate);

  double Convexity() const { return convexity; }
  double& Convexity() { return convexity; }

  double Lipschitz() const { return lipschitz; }
  double& Lipschitz() { return lipschitz; }

  size_t BatchSize() const { return batchSize; }
  size_t& BatchSize() { return batchSize; }

  size_t MaxIterations() const { return maxIterations; }
  size_t& MaxIterations() { return maxIterations; }

  size_t InnerIterations() const { return innerIterations; }
  size_t& InnerIterations() { return innerIterations; }

  double Tolerance() const { return tolerance; }
  double& Tolerance() { return tolerance; }

  bool Shuffle() const { return shuffle; }
  bool& Shuffle() { return shuffle; }

 private:
  double convexity;

  double lipschitz;

  size_t batchSize;

  size_t maxIterations;

  size_t innerIterations;

  double tolerance;

  bool shuffle;
};

// Convenience typedefs.

using Katyusha = KatyushaType<false>;

using KatyushaProximal = KatyushaType<true>;

} // namespace optimization
} // namespace mlpack

// Include implementation.
#include "katyusha_impl.hpp"

#endif