void KernelModel::setKernel (const vectord &thetav,
const vectord &stheta,
std::string k_name,
size_t dim)
{
KernelFactory mKFactory;
mKernel.reset(mKFactory.create(k_name, dim));
if ((thetav.size() == 1) && (stheta.size() == 1) && (mKernel->nHyperParameters() != 1))
{
// We assume isotropic prior, so we replicate the vectors for all dimensions
size_t n = mKernel->nHyperParameters();
FILE_LOG(logINFO) << "Expected " << n << " hyperparameters."
<< " Replicating parameters and prior.";
vectord newthetav = svectord(n,thetav(0));
vectord newstheta = svectord(n,stheta(0));
setKernelPrior(newthetav,newstheta);
mKernel->setHyperParameters(newthetav);
}
else
{
setKernelPrior(thetav,stheta);
mKernel->setHyperParameters(thetav);
}
}
NLOPT_Optimization::NLOPT_Optimization(RGBOptimizable* rgbo, size_t dim):
mDown(dim),mUp(dim)
{
rbobj = NULL; rgbobj = new RGBOptimizableWrapper(rgbo);
alg = DIRECT; maxEvals = MAX_INNER_EVALUATIONS;
setLimits(zvectord(dim),svectord(dim,1.0));
};
int GP_Hedge::update_hedge()
{
// We just care about the differences
double max_l = *std::max_element(loss_.begin(),loss_.end());
loss_ += svectord(loss_.size(),max_l);
// To avoid overflow
double mean_g = std::accumulate(gain_.begin(),gain_.end(),0.0)
/ static_cast<double>(gain_.size());
gain_ -= svectord(gain_.size(),mean_g);
// Optimal eta according to Shapire
double max_g = *std::max_element(gain_.begin(),gain_.end());
double eta = (std::min)(10.0,sqrt(2.0*log(3.0)/max_g));
// Compute probabilities
std::transform(gain_.begin(), gain_.end(), prob_.begin(),
boost::bind(softmax,_1,eta));
//Normalize
double sum_p =std::accumulate(prob_.begin(),prob_.end(),0.0);
prob_ /= sum_p;
//Update bandits gain
gain_ -= loss_;
std::partial_sum(prob_.begin(), prob_.end(), cumprob_.begin(),
std::plus<double>());
randFloat sampleUniform( *mtRandom, realUniformDist(0,1));
double u = sampleUniform();
for (size_t i=0; i < cumprob_.size(); ++i)
{
if (u < cumprob_(i))
return i;
}
FILE_LOG(logERROR) << "Error updating Hedge algorithm. "
<< "Selecting first criteria by default.";
return 0;
};