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The Gaussian Surface Area and Noise Sensitivity of Degree-d Polynomial Threshold Functions

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1 Author(s)
Kane, D.M. ; Dept. of Math., Harvard Univ., Cambridge, MA, USA

We prove asymptotically optimal bounds on the Gaussian noise sensitivity of degree-d polynomial threshold functions. These bounds translate into optimal bounds on the Gaussian surface area of such functions, and therefore imply new bounds on the running time of agnostic learning algorithms.

Published in:

Computational Complexity (CCC), 2010 IEEE 25th Annual Conference on

Date of Conference:

9-12 June 2010

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