The Wrong Direction of Jensen’s Inequality Is Algorithmically Right

Zamir, Or

doi:10.4230/LIPIcs.ICALP.2023.107

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LIPIcs.ICALP.2023.107.pdf

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Document Identifiers

DOI: 10.4230/LIPIcs.ICALP.2023.107
URN: urn:nbn:de:0030-drops-181593

Author Details

Or Zamir

Princeton University, NJ, USA

Acknowledgements

The author would like to thank Avi Wigderson for pointing out important references.

Cite AsGet BibTex

Or Zamir. The Wrong Direction of Jensen’s Inequality Is Algorithmically Right. In 50th International Colloquium on Automata, Languages, and Programming (ICALP 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 261, pp. 107:1-107:10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)
https://doi.org/10.4230/LIPIcs.ICALP.2023.107

Abstract

Let 𝒜 be an algorithm with expected running time e^X, conditioned on the value of some random variable X. We construct an algorithm A' with expected running time O (e^𝖤[X]), that fully executes 𝒜. In particular, an algorithm whose running time is a random variable T can be converted to one with expected running time O (e^𝖤[ln T]), which is never worse than O(𝖤[T]). No information about the distribution of X is required for the construction of 𝒜'.

Subject Classification

ACM Subject Classification

Theory of computation → Parameterized complexity and exact algorithms
Theory of computation → Algorithm design techniques
Theory of computation → Computational complexity and cryptography

Keywords

algorithms
complexity
Jensen’s inequality

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References

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