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On Learning Monotone DNF Formulae under Uniform Distributions

โœ Scribed by L. Kucera; A. Marchettispaccamela; M. Protasi


Book ID
112252070
Publisher
Elsevier Science
Year
1994
Tongue
English
Weight
443 KB
Volume
110
Category
Article
ISSN
0890-5401

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We show that a DNF with terms of size at most \(d\) can be approximated by a function at most \(d^{O(d \log 1 / \epsilon)}\) nonzero Fourier coefficients such that the expected error squared, with respect to the uniform distribution, is at most \(\epsilon\). This property is used to derive a learnin