[MRG] Sample weights for gradient boosting

and piggy-packed ``'exponential'`` loss for binary classification (= AdaBoost).

~~I didn't implement sample weights for ``'lad'``, ``'huber'``, and ``'quantile'`` since it would require weighted median / percentiles. I will either raise a warning or exception in this case: what do you prefer?~~

cc @glouppe

TODO: ~~benchmark benchmark and some regression tests~~
added 2 * ones and compared all three to make sure we create the same predictions; huber loss failed so I assume I have an error in the weight updates. I adapted that formula without calculating the update myself - will do.