Implement generic proximal Newton solver for solving nonsmooth minimization problems

This commit add a generic proximal Newton solver to solve non-smooth minimization problems of the form

min `J(x) = f(x) + g(x)`

where f is a smooth C^2 function and g is possibly non-smooth. The algorithm is based on the `Solvers::LoopSolver` and inherits from `Solvers::Solver`.
During the `solve()` call increments of the second order subproblems

min `0.5*f''(x)[dx,dx] + f'(x)[dx] + g(x + dx) + r||dx||^2`

are computed and the iterate is updated by `x := x + dx`. Details and documentation are provided at the class definition.

A simple test case is added which solves a minimization problem with an analytical solution.