[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~~
Loss was added for completeness -- from an algorithm point of view I'd suggest that users rather use ``AdaBoostClassifier``, however, I havent benchmarked the two implementations against each other. I should do that...