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However, because we want to evaluate the similarity between the original model and the approximate model, I think the correct formula should be as follows:
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I simply implemented the algorithm appear in Fig.1 in this paper, and I suppose rho is derived with some approximations. Although the formula you provided may be better, I'm not very sure. Note that this part brings only a very small difference in convergence speed.
Thanks for the wonderful work!!
When I read the source code, I was confused by the calculation of
rho
in this line. I'll paste it here.double rho = (y0 - yi) / (d.dot(lm_lambda_ * d - b));
However, because we want to evaluate the similarity between the original model and the approximate model, I think the correct formula should be as follows:
double rho = (y0 - yi) / (d.dot((H + lm_lambda_ * Eigen::Matrix<double, 6, 6>::Identity()) * d + 2 * b)) * (-1.0);
I will attach my proof here.
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