. We consider the exact learnability of subclasses of Boolean formulas from membership queries alone. We show how to combine known learning algorithms that use membership and equivalence queries to obtain new learning results only with memberships. In particular we show the exact learnability of read-k monotone CDNF formulas, Sat- k O(log n)-CDNF, and O( p log n)-size CDNF from membership queries only. 1 Introduction Learning DNF formulas has been one of the most attractive and tantalizing problems since the seminal paper of Valiant [Val84]. Although many results in the literature give evidence that the problem is hard even if we are allow to use membership queries [AK91, AHP92], it has been recently proved by Jackson [Jac94] that using membership queries, DNF are PAC learnable in polynomial time under the uniform distribution. Here we concentrate in a more restricted framework. While Jackson's algorithm is a PAC learning algorithm, we wish to have exact identification of the target..
