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License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.APPROX/RANDOM.2020.28
URN: urn:nbn:de:0030-drops-126316
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2020/12631/
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Ben-David, Shalev ; Göös, Mika ; Kothari, Robin ; Watson, Thomas

When Is Amplification Necessary for Composition in Randomized Query Complexity?

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LIPIcs-APPROX28.pdf (0.6 MB)

Abstract

Suppose we have randomized decision trees for an outer function f and an inner function g. The natural approach for obtaining a randomized decision tree for the composed function (f∘ gⁿ)(x¹,…,xⁿ) = f(g(x¹),…,g(xⁿ)) involves amplifying the success probability of the decision tree for g, so that a union bound can be used to bound the error probability over all the coordinates. The amplification introduces a logarithmic factor cost overhead. We study the question: When is this log factor necessary? We show that when the outer function is parity or majority, the log factor can be necessary, even for models that are more powerful than plain randomized decision trees. Our results are related to, but qualitatively strengthen in various ways, known results about decision trees with noisy inputs.

BibTeX - Entry

@InProceedings{bendavid_et_al:LIPIcs:2020:12631,
  author =	{Shalev Ben-David and Mika G{\"o}{\"o}s and Robin Kothari and Thomas Watson},
  title =	{{When Is Amplification Necessary for Composition in Randomized Query Complexity?}},
  booktitle =	{Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2020)},
  pages =	{28:1--28:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-164-1},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{176},
  editor =	{Jaros{\l}aw Byrka and Raghu Meka},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2020/12631},
  URN =		{urn:nbn:de:0030-drops-126316},
  doi =		{10.4230/LIPIcs.APPROX/RANDOM.2020.28},
  annote =	{Keywords: Amplification, composition, query complexity}
}

Keywords: Amplification, composition, query complexity
Collection: Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2020)
Issue Date: 2020
Date of publication: 11.08.2020

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