… approach the DNF learning problem by representing a DNF formula as … time algorithms for
learning linear threshold functions to learn polynomial threshold functions of degree d in time …

… Moreover, without any noise an AND formula can be properly learnt in polynomial time. Our
reduction proves an equivalent result for learning OR by t-DNF, ie DNF formula with at most t …

… queries to learn the class of k-term DNF formulas in time O(n•… one to learn DNF of O(log
n) terms in polynomial time. We … The algorithm is an exact learning algorithm, but one where …

… learning models ([3, 9, 14, 13, 18, 19, 22, 26, 27, 4, 6]). Here we present new results on learning
DNF formulas, using DNF … n-term DNF formulas can be learned in polynomial time in the …

… used to weakly learn DNF using membership queries in polynomial time, with respect …
learning unrestricted DNF expressions in polynomial time in any nontrivial formal model of learning…

We show that a DNF with terms of size at most d can be approximated by a function with at
most … learns a DNF with a polynomial number of terms in time n O(log log n) , and a DNF with …

… many learning problems can be reduced to learning Boolean functions, in many cases a
more efficient learning … In this paper we give a natural generalization of DNF formulas, ZN-DNF …

… #DNF, an approach that combines deep learning and approximate model counting and
enables fast weighted #DNF … We show running times for the GNN vs. KLM (ϵ = 0.1, δ = 0.05) for …

… time bounds for learning DNF continue to hold in the presence of classification noise. In fact,
in [9] a polynomial time algorithm is given for learning … n) time bound for learning DNF holds …

… to learn DNF. In the PAC model, Jackson [13] has given an algorithm using membership
queries to learn DNF … in polynomial time in the query learning model, even by a randomized …