rlsprimalr.h

 /*
  * The GURLS Package in C++
  *
  * Copyright (C) 2011-1013, IIT@MIT Lab
  * All rights reserved.
  *
  * authors:  M. Santoro
  * email:   msantoro@mit.edu
  * website: http://cbcl.mit.edu/IIT@MIT/IIT@MIT.html
  *
  * Redistribution and use in source and binary forms, with or without
  * modification, are permitted provided that the following conditions
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#ifndef _GURLS_RLSPRIMALR_H_
#define _GURLS_RLSPRIMALR_H_

#include "gurls++/optimization.h"
#include "gurls++/gmath.h"
#include "gurls++/utils.h"

namespace gurls {

template <typename T>
class RLSPrimalr: public Optimizer<T>{

public:
    GurlsOptionsList* execute(const gMat2D<T>& X, const gMat2D<T>& Y, const GurlsOptionsList& opt);
};


template <typename T>
GurlsOptionsList* RLSPrimalr<T>::execute(const gMat2D<T>& X, const gMat2D<T>& Y, const GurlsOptionsList& opt)
{
    //  lambda = opt.singlelambda(opt.paramsel.lambdas);
    const gMat2D<T> &ll = opt.getOptValue<OptMatrix<gMat2D<T> > >("paramsel.lambdas");
    T lambda = opt.getOptAs<OptFunction>("singlelambda")->getValue(ll.getData(), ll.getSize());


//    std::cout << "Solving primal RLS using Randomized SVD..." << std::endl;

    //  [n,d] = size(X);

    const unsigned long n = X.rows();
    const unsigned long d = X.cols();

    const unsigned long Yn = Y.rows();
    const unsigned long Yd = Y.cols();

    //  ===================================== Primal K

//  XtX = X'*X;
    T* XtX = new T[d*d];
    dot(X.getData(), X.getData(), XtX, n, d, n, d, d, d, CblasTrans, CblasNoTrans, CblasColMajor);


//    [Q,L,U] = tygert_svd(XtX,d);
//    Q = double(Q);
//    L = double(diag(L));
    T *Q = new T[d*d];
    T *L = new T[d];
    T *V = NULL;

    unsigned long k = static_cast<unsigned long>(gurls::round((opt.getOptAsNumber("eig_percentage")*d)/100.0));
    random_svd(XtX, d, d, Q, L, V, k);

    delete[] XtX;

//  Xty = X'*y;
    T* Xty = new T[d*Yd];
    dot(X.getData(), Y.getData(), Xty, n, d, Yn, Yd, d, Yd, CblasTrans, CblasNoTrans, CblasColMajor);

//    if isfield(opt,'W0')
    if(opt.hasOpt("W0"))
    {
//        Xty = Xty + opt.W0;
        const gMat2D<T>& W0 = OptMatrix< gMat2D<T> >::dynacast(opt.getOpt("W0"))->getValue();

        if(W0.rows() == d && W0.cols() == Yd)
            axpy(d*Yd, (T)1.0, W0.getData(), 1, Xty, 1);
    }


    T* QtXty = new T[d*Yd];
    dot(Q, Xty, QtXty, d, d, d, Yd, d, Yd, CblasTrans, CblasNoTrans, CblasColMajor);

//    cfr.W = rls_eigen(Q, L, Q'*Xty, lambda,d);
    gMat2D<T>* W = new gMat2D<T>(d, Yd);
    T* work = new T[d*(d+1)];
    rls_eigen(Q, L, QtXty, W->getData(), lambda, d, d, d, d, d, Yd, work);


    delete [] QtXty;
    delete [] work;
    delete [] Xty;
    delete [] Q;
    delete [] L;

    GurlsOptionsList* optimizer = new GurlsOptionsList("optimizer");

    optimizer->addOpt("W", new OptMatrix<gMat2D<T> >(*W));

//    cfr.C = [];
    gMat2D<T>* emptyC = new gMat2D<T>();
    optimizer->addOpt("C", new OptMatrix<gMat2D<T> >(*emptyC));

    //  cfr.X = [];
    gMat2D<T>* emptyX = new gMat2D<T>();
    optimizer->addOpt("X", new OptMatrix<gMat2D<T> >(*emptyX));

    return optimizer;
}


}
#endif // _GURLS_RLSPRIMALR_H_