We study exact active learning of binary and multiclass classifiers with margin. Given an n-point set X ⊂ℝ^m, we want to learn any unknown classifier on X whose classes have finite strong convex hull margin, a new notion extending the SVM margin.In the standard active learning setting, where only label queries are allowed, learning a classifier with strong convex hull margin γ requires in the worst case Ω(1+1/γ)^m-1/2 queries. On the other hand, using the more powerful seed queries (a variant of…