Date of Original Version
9-2004
Type
Article
Published In
Journal of Computer and System Sciences Volume 71, Issue 3, October 2005, Pages 250-265
Abstract or Table of Contents
We consider a model of learning Boolean functions from examples generated by a uniform random walk on {0,1}n. We give a polynomial time algorithm for learning decision trees and DNF formulas in this model. This is the first efficient algorithm for learning these classes in a natural passive learning model where the learner has no influence over the choice of examples used for learning.