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Random Structures and Algorithms
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Random Structures and Algorithms
Article . 2018 . Peer-reviewed
License: Wiley Online Library User Agreement
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DBLP
Article . 2021
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On polynomial approximations to AC

Authors: Prahladh Harsha; Srikanth Srinivasan 0001;

On polynomial approximations to AC

Abstract

AbstractClassicalapproximation results show that anycircuit of sizeand depthhas an‐error probabilistic polynomial over the reals of degree. We improve this upper bound to, which is much better for small values of. We then use this result to show that‐wise independence foolscircuits of sizeand depthup to error at most, improving on Tal's strengthening of Braverman's result that‐wise independence suffices. To our knowledge, this is the first PRG construction forthat achieves optimal dependence on the error. We also prove lower bounds on the best polynomial approximations to. We show that any polynomial approximating thefunction onbits to a small constant error must have degree at least. This result improves exponentially on a result of Meka, Nguyen, and Vu (Theory Comput. 2016).

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Top 10%
Average
Top 10%
hybrid