research-article

Separation between Estimation and Approximation

Authors:

Shlomo JozephAuthors Info & Claims

ITCS '15: Proceedings of the 2015 Conference on Innovations in Theoretical Computer Science

Pages 271 - 276

https://doi.org/10.1145/2688073.2688101

Published: 11 January 2015 Publication History

Abstract

We show (under standard assumptions) that there are \textsf{NP} optimization problems for which estimation is easier than approximation. Namely, one can estimate the value of the optimal solution within a ratio of $\rho$, but it is difficult to find a solution whose value is within $\rho$ of optimal. As an important special case, we show that there are linear programming relaxations for which no polynomial time rounding technique matches the integrality gap of the linear program.

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Cited By

Krauthgamer RReitblat D(2022)Almost-Smooth Histograms and Sliding-Window Graph AlgorithmsAlgorithmica10.1007/s00453-022-00988-y84:10(2926-2953)Online publication date: 24-Jun-2022
https://doi.org/10.1007/s00453-022-00988-y
Jansen KRohwedder LKlein P(2017)On the configuration-LP of the restricted assignment problemProceedings of the Twenty-Eighth Annual ACM-SIAM Symposium on Discrete Algorithms10.5555/3039686.3039862(2670-2678)Online publication date: 16-Jan-2017
https://dl.acm.org/doi/10.5555/3039686.3039862

Index Terms

Separation between Estimation and Approximation
1. Theory of computation
  1. Computational complexity and cryptography
    1. Complexity classes
  2. Design and analysis of algorithms

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cover image ACM Conferences

ITCS '15: Proceedings of the 2015 Conference on Innovations in Theoretical Computer Science

January 2015

404 pages

ISBN:9781450333337

DOI:10.1145/2688073

Program Chair:
Tim Roughgarden
Stanford University

Copyright © 2015 ACM.

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Published: 11 January 2015

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Israel Science Foundation

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ITCS'15

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SIGACT

ITCS'15: Innovations in Theoretical Computer Science

January 11 - 13, 2015

Rehovot, Israel

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ITCS '15 Paper Acceptance Rate 45 of 159 submissions, 28%;

Overall Acceptance Rate 172 of 513 submissions, 34%

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Cited By

Krauthgamer RReitblat D(2022)Almost-Smooth Histograms and Sliding-Window Graph AlgorithmsAlgorithmica10.1007/s00453-022-00988-y84:10(2926-2953)Online publication date: 24-Jun-2022
https://doi.org/10.1007/s00453-022-00988-y
Jansen KRohwedder LKlein P(2017)On the configuration-LP of the restricted assignment problemProceedings of the Twenty-Eighth Annual ACM-SIAM Symposium on Discrete Algorithms10.5555/3039686.3039862(2670-2678)Online publication date: 16-Jan-2017
https://dl.acm.org/doi/10.5555/3039686.3039862

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