Merve Unuvar, Yurdaer Doganata, et al.
CLOUD 2014
We present results concerning the learning of Monotone DNF (MDNF) from Incomplete Membership Queries and Equivalence Queries. Our main result is a new algorithm that allows efficient learning of MDNF using Equivalence Queries and Incomplete Membership Queries with probability of p = 1 - 1/poly(n, t) of failing. Our algorithm is expected to make O((tn/1 - p)2) queries, when learning a MDNF formula with t terms over n variables. Note that this is polynomial for any failure probability p = 1 - 1/poly(n, t). The algorithm's running time is also polynomial in t, n, and 1/(1 - p). In a sense this is the best possible, as learning with p = 1 - 1/ω(poly(n, t)) would imply learning MDNF, and thus also DNF, from equivalence queries alone.
Merve Unuvar, Yurdaer Doganata, et al.
CLOUD 2014
Els van Herreweghen, Uta Wille
USENIX Workshop on Smartcard Technology 1999
Tim Erdmann, Stefan Zecevic, et al.
ACS Spring 2024
Kenneth L. Clarkson, Elad Hazan, et al.
Journal of the ACM