Add first version of the Riemannian Proximal Newton solver, as an alternative to the Trust-Region Solver.

In each step of these two iterative solvers, we try to find a correction
that decreases the energy of the nonlinear functional of the current iterate x.
The correction is calculated using the Taylor expansion around x,
resulting in the problem: Hessian(x) * correction = -gradient(x).
Within a certain radius around x, the functional can be approximated correctly and then
the corrections causes an energy decrease.
1) The trust-region algorithm ensures this using a trust-region.
2) The proximal newton method ensures this by punishing
   large corrections using a regularization factor.