Parameterized learnability of juntas

We study the parameterized complexity of learning k-juntas and some variations of juntas. We show the hardness of learning k-juntas and subclasses of k-juntas in the PAC model by reductions from a -complete problem. On the other hand, as a consequence of a more general result, we show that k-juntas are exactly learnable with improper equivalence queries and access to a oracle.