Difference between revisions of "Polynomial threshold"
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* The [[influence | total influence]] of a degree-<math>k</math> polynomial threshold function is bounded by <math>2^{O(d)}O(n^{1-1/(4k+6)})</math>. <ref>Prahladh Harsha, Adam Klivans, Raghu Meka, [http://theoryofcomputing.org/articles/v010a001/v010a001.pdf Bounding the Sensitivity of Polynomial Threshold Functions], Theorem 1.6</ref> | * The [[influence | total influence]] of a degree-<math>k</math> polynomial threshold function is bounded by <math>2^{O(d)}O(n^{1-1/(4k+6)})</math>. <ref>Prahladh Harsha, Adam Klivans, Raghu Meka, [http://theoryofcomputing.org/articles/v010a001/v010a001.pdf Bounding the Sensitivity of Polynomial Threshold Functions], Theorem 1.6</ref> | ||
* The [[noise sensitivity]] of a degree-<math>k</math> polynomial threshold function, when the noise is of rate <math>\delta</math>, is at most <math>2^{O(d)}O(\delta^{1/(4k+6)})</math>. <ref>Prahladh Harsha, Adam Klivans, Raghu Meka, [http://theoryofcomputing.org/articles/v010a001/v010a001.pdf Bounding the Sensitivity of Polynomial Threshold Functions], Theorem 1.3</ref> | * The [[noise sensitivity]] of a degree-<math>k</math> polynomial threshold function, when the noise is of rate <math>\delta</math>, is at most <math>2^{O(d)}O(\delta^{1/(4k+6)})</math>. <ref>Prahladh Harsha, Adam Klivans, Raghu Meka, [http://theoryofcomputing.org/articles/v010a001/v010a001.pdf Bounding the Sensitivity of Polynomial Threshold Functions], Theorem 1.3</ref> | ||
| − | * TODO: proposition 5.6 in O'Donnell says that functions with small noise sensitivity are close to low degree polynomial thresholds. | + | * TODO: proposition 5.6 in O'Donnell says that functions with small noise sensitivity are close to low degree polynomial thresholds. |
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== Conjectures == | == Conjectures == | ||
Latest revision as of 14:08, 5 April 2021
Definition
A function [math]f:\{-1,1\}^n \to \{-1,1\}[/math] is called a polynomial threshold function of degree at most [math]k[/math] if there exists a real polynomial [math]p(x)[/math] of degree at most [math]k[/math] such that [math]f(x) = \mathrm{sign}(p(x))[/math].
The special case [math]k = 1[/math] is of special interest; it is the linear threshold function.
Properties
- The total influence of a degree-[math]k[/math] polynomial threshold function is bounded by [math]2^{O(d)}O(n^{1-1/(4k+6)})[/math]. [1]
- The noise sensitivity of a degree-[math]k[/math] polynomial threshold function, when the noise is of rate [math]\delta[/math], is at most [math]2^{O(d)}O(\delta^{1/(4k+6)})[/math]. [2]
- TODO: proposition 5.6 in O'Donnell says that functions with small noise sensitivity are close to low degree polynomial thresholds.
Conjectures
- Gotsman and Linial [13] conjectured, for example,that the average sensitivity of a degree-dpolynomial isO(d√n). (TODO: this is from Harsha at el paper, please cite properly, just here for keepsies)
References
- ↑ Prahladh Harsha, Adam Klivans, Raghu Meka, Bounding the Sensitivity of Polynomial Threshold Functions, Theorem 1.6
- ↑ Prahladh Harsha, Adam Klivans, Raghu Meka, Bounding the Sensitivity of Polynomial Threshold Functions, Theorem 1.3
