4 ms·
Newton's method finds zeros of functions, which is different from optimisation (finding maximums or minimums). If you use Newton's method on a function which i
by mkl 8y ago
Newton's method finds zeros of functions, which is different from optimisation (finding maximums or minimums). If you use Newton's method on a function which is the derivative of some other function you're trying to optimise, then it will find critical points, which may be the optimums you're looking for (or inflection points, saddles, etc.).
- deleted 8y ago[deleted]
- deleted 8y ago[deleted]
- snovv_crash 8y agoThis is why you actually do something like Levenberg-Marquardt, which combines a gradient descent with a trust region of quadratic optimization, which is varied depending on if the cost function is decreasing or not. And of course it is iterative, so a single bad step doesn't destroy everything. The advantage comes from faster convergence in practice.
- mi_lk 8y agoDo you know of any good literature on LM or trust region? I'm interested in the details.
- snovv_crash 8y agoI strongly recommend reading the documentation for Ceres Solver [1]. It is intuitive and in-depth, and references everything you will need. 1. http://ceres-solver.org/nnls_solving.html#trust-region-methods http://ceres-solver.org/nnls_solving.html#trust-region-metho...