[MRG+2] 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~~
Maybe you can do a loop over all the classification losses. It might be good to forge a similar edge case test for regression losses.