This PR add several solvers for regularized OT from the following paper:

Blondel, M., Seguy, V., & Rolet, A. (2018). Smooth and Sparse Optimal Transport. Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics (AISTATS).

Some of the code come from https://github.com/mblondel/smooth-ot/

List of new stuff:

• Solvers for smooty dual and semi dual for negentropy and squared L2 regularization
• Wrapper functions smooth_ot_dual and smooth_ot_semi_dual compatible with ot.sinkhorn.
• Detailed dosumentation about the optimization problems.
• Several test for all regularizations.
• Example of use code in plot_OT_1D_smooth.py
• Update readme with new feature and reference.

Here is an example of 1D OT matrix for squared L2 regularization.