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/dports/science/pybrain/pybrain-0.3.3/pybrain/auxiliary/
H A Dgradientdescent.py136 self.previous_gradient = zeros(values.shape)
141 products = self.previous_gradient * gradient
164 self.previous_gradient = gradient
/dports/math/py-iminuit/iminuit-2.8.4/extern/root/math/minuit2/src/
H A DNumericalDerivator.cxx155 const std::vector<DerivatorElement> &previous_gradient) in Differentiate() argument
163 gradient.emplace_back(FastPartialDerivative(function, parameters, ix, previous_gradient[ix])); in Differentiate()
/dports/math/py-iminuit/iminuit-2.8.4/extern/root/math/minuit2/inc/Minuit2/
H A DNumericalDerivator.h51 … const std::vector<DerivatorElement> &previous_gradient);
/dports/biology/hyphy/hyphy-2.5.33/src/core/
H A Dlikefunc.cpp6417 previous_gradient; local
6449 previous_gradient = gradient;
6464 scalar_product += previous_gradient.theData[i] * previous_gradient.theData[i];
6465 beta += gradient.theData[i] * ( previous_gradient.theData[i] - gradient.theData[i]);
6493 previous_gradient = previous_direction;
6494 previous_gradient *= beta;
6497 current_direction += previous_gradient;