111     gradient_.resize(n, 1);  in ComputeStep()
175   gradient_.setZero();  in ComputeGradient()
176   jacobian->LeftMultiply(residuals, gradient_.data());  in ComputeGradient()
177   gradient_.array() /= diagonal_.array();  in ComputeGradient()
189       (gradient_.array() / diagonal_.array()).matrix();  in ComputeCauchyPoint()
191   alpha_ = gradient_.squaredNorm() / Jg.squaredNorm();  in ComputeCauchyPoint()
200   VectorRef dogleg_step(dogleg, gradient_.rows());  in ComputeTraditionalDoglegStep()
204   const double gradient_norm = gradient_.norm();  in ComputeTraditionalDoglegStep()
219     dogleg_step = -(radius_ / gradient_norm) * gradient_;  in ComputeTraditionalDoglegStep()
234   const double b_dot_a = -alpha_ * gradient_.dot(gauss_newton_step_);  in ComputeTraditionalDoglegStep()
249   dogleg_step = (-alpha_ * (1.0 - beta)) * gradient_  in ComputeTraditionalDoglegStep()
267   VectorRef dogleg_step(dogleg, gradient_.rows());  in ComputeSubspaceDoglegStep()
311     dogleg_step = -(radius_ / gradient_.norm()) * gradient_;  in ComputeSubspaceDoglegStep()
649   basis_vectors.col(0) = gradient_;  in ComputeSubspaceModel()
700   subspace_g_ = subspace_basis_.transpose() * gradient_;  in ComputeSubspaceModel()