void UpdateWeights(MatType& weights,
const MatType& gradient,
const double /* unused */)
{
MatType derivs = gradient % prevDerivs;
for (size_t i(0); i < derivs.n_cols; i++)
{
for (size_t j(0); j < derivs.n_rows; j++)
{
if (derivs(j, i) > 0)
{
updateValues(j, i) = std::min(updateValues(j, i) * etaPlus, maxDelta);
prevWeightChange(j, i) = boost::math::sign(gradient(j, i)) * updateValues(j, i);
prevDerivs(j, i) = gradient(j, i);
}
else if (derivs(j, i) < 0)
{
updateValues(j, i) = std::max(updateValues(j, i) * etaMin, minDelta);
prevDerivs(j, i) = 0;
}
else
{
prevWeightChange(j, i) = boost::math::sign(gradient(j, i)) * updateValues(j, i);
prevDerivs(j, i) = gradient(j, i);
}
weights(j, i) -= prevWeightChange(j, i);
}
}
}
void UpdateWeights(MatType& weights,
const MatType& gradient,
const double /* unused */)
{
MatType derivs = gradient % prevDerivs;
for (size_t i(0); i < derivs.n_cols; i++)
{
for (size_t j(0); j < derivs.n_rows; j++)
{
if (derivs(j, i) >= 0)
{
prevDelta(j, i) = std::min(prevDelta(j, i) * etaPlus, maxDelta);
prevDerivs(j, i) = gradient(j, i);
}
else
{
prevDelta(j, i) = std::max(prevDelta(j, i) * etaMin, minDelta);
prevDerivs(j, i) = 0;
}
}
}
weights -= arma::sign(gradient) % prevDelta;
}
