[WIP] Strong rules for coordinate descent

Fixes https://github.com/scikit-learn/scikit-learn/issues/229

This implements strong rules for discarding non active features in coordinate descent. I believe this works. However it is really slow. 

TODO:

- [ ] Decide whether to migrate the strong_active_set and check_kkt_conditions to Cython
- [ ] Fix the lazy centering of sparse matrices that gives slightly different results.
It took me some time to finally understood the difference between `E` and `A(lambda)` . I was thinking that both "add these predictors into E" and "add these predictors into A(lambda)" mean the same thing.