Luis Pineda

Hi @jeffin07, yes this is open!

Awesome! The idea would be to implement [this](https://en.wikipedia.org/wiki/Powell%27s_dog_leg_method) optimization method. As a guide, you can use the code for [Gauss-Newton](https://github.com/facebookresearch/theseus/blob/main/theseus/optimizer/nonlinear/gauss_newton.py#L43). This function computes \delta_{gn} in the link above. Note that...

Hi @jeffin07, that's correct, delta_gn is just `delta_gn = self.linear_solver.solve()`. For the easiest example of how the linear solvers do this computation, you can check [here](https://github.com/facebookresearch/theseus/blob/main/theseus/optimizer/linear/dense_solver.py#L113), and the `_solve_system` method...

Hi @jeffin07, I'm really sorry, somehow I missed this comment until today. I also noticed my previous comment was not entirely accurate, the return value should follow this: 

Hi @jeffin07. I was wondering if you were blocked on this and if there was anything we could do to help. In case it's useful, the dogleg implementation of GTSAM...

In their code, the input `delta` refers to the trust region radius, which we can probably keep as a member variable (of type tensor, for handling batches)*. The other two...

Do you have an example where `dim` is not consistent with the dimension of the error returned? I've fixed this error in some cost functions before, but maybe I missed...

Ah, I think this particular instance was fixed in experimental branch but never merged to main, if I recall correctly. Let's leave this feature request open until we add some...

Good catch, @bamos! I was just playing around with something like `y = a * exp(-b * x)`, and the issue persists; I guess once the inner opt finishes, for...

I was actually thinking that we can probably achieve the desired behavior with a single optimization problem, by tweaking the example @bamos wrote in #26. Basically we fix `a_target` and...