[MRG+1] TheilSen robust linear regression

A multiple linear Theil-Sen regression for the Scikit-Learn toolbox. The implementation is based on the algorithm from the paper "Theil-Sen Estimators in a Multiple Linear Regression Model" of Xin Dang, Hanxiang Peng, Xueqin Wang and Heping Zhang. It is parallelized with the help of joblib.
On a personal note, I think that the popular Theil-Sen regression would be a nice addition to Scikit-Learn.
I am looking forward to your feedback. 

Florian
This new metric is a separate contribution from the Theil Sen estimator. So I suggest that you extract the median squared error contribution from this pull request and made a new pr for that one.

As a new regression metric, it should
   - be added to the list of regression metrics in `doc/modules/classes.rst`
   - have a narrative documenation in `doc/module/model_evalution.rst`
   - have test to ensure correctness in `sklearn/metrics/tests/test_regression.py`
   - pass invariant tests from `sklearn/metrics/tests/test_common.py`

The doctest is nice to show how it works, but we don't use them as tests.