Worst Case to Average Case Reductions for Polynomials

dc.creatorKaufman, Tali
dc.creatorLovett, Shachar
dc.date2008-06-27
dc.date2008-07-02
dc.date.accessioned2026-07-07T09:47:50Z
dc.date.available2026-07-07T09:47:50Z
dc.descriptionA degree-$d$ polynomial $p$ in $n$ variables over a field $\F$ is {\em equidistributed} if it takes on each of its $|\F|$ values close to equally often, and {\em biased} otherwise. We say that $p$ has a {\em low rank} if it can be expressed as a bounded combination of polynomials of lower degree. Green and Tao [gt07] have shown that bias imply low rank over large fields (i.e. for the case $d < |\F|$). They have also conjectured that bias imply low rank over general fields. In this work we affirmatively answer their conjecture. Using this result we obtain a general worst case to average case reductions for polynomials. That is, we show that a polynomial that can be {\em approximated} by few polynomials of bounded degree, can be {\em computed} by few polynomials of bounded degree. We derive some relations between our results to the construction of pseudorandom generators, and to the question of testing concise representations.
dc.identifierhttps://arxiv.org/abs/0806.4535
dc.identifierhttp://arxiv.org/abs/0806.4535
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/163993
dc.subjectCombinatorics
dc.titleWorst Case to Average Case Reductions for Polynomials
dc.typetext

Files

Collections