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Learning DNF from random walks

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4 Author(s)
Bshouty, N. ; Dept. of Comput. Sci., Technion, Haifa, Israel ; Mossel, E. ; O'Donnell, R. ; Servedio, R.A.

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.

Published in:

Foundations of Computer Science, 2003. Proceedings. 44th Annual IEEE Symposium on

Date of Conference:

11-14 Oct. 2003

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