Learning by extended statistical queries and its relation to PAC learning

PAC learning from examples is factored so that (i) the membership queries are used to evaluate empirically “statistical queries” — certain expectations of functionals involving the unknown target. (ii) approximate value of these statistical queries are used to compute an output — an approximation of the target.