[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~~
fail... thanks @glouppe -- added a test for all loss functions to make sure that deviance supports both sample weights and None