our margin adaboost itself does not sign gradient method commonly used now the save on communication this gets you some L infinity bias and of course gradient descent is steepest descent with respect to l2 okay so that's kind of that's great we understand logistic regression very well that's sort of always the starting point so now the question is what does it do on deep networks if you're if you're very very very optimistic you may hope that it solves max margin even if you do know regularization because then you will