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  /frameworks/ml/bordeaux/learning/stochastic_linear_ranker/native/
stochastic_linear_ranker.cpp 38 const double gradient_norm = gradient.L2Norm(); local
41 if (gradient_norm < kMinGradientNorm || gradient_norm > kMaxGradientNorm)
45 std::min(lambda_, loss / (gradient_norm * gradient_norm));
48 loss / (gradient_norm * gradient_norm + 1 / (2 * lambda_));
  /external/ceres-solver/internal/ceres/
dogleg_strategy.cc 199 const double gradient_norm = gradient_.norm(); local
213 if (gradient_norm * alpha_ >= radius_) {
214 dogleg_step = -(radius_ / gradient_norm) * gradient_;
230 const double a_squared_norm = pow(alpha_ * gradient_norm, 2.0);

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