One-shot multivariate covering lemmas via weighted sum and concentration inequalities

Mohammad H. Yassaee; Jingbo Liu; Sergio Verdu

doi:10.1109/ISIT.2017.8006612

One-shot multivariate covering lemmas via weighted sum and concentration inequalities

Mohammad H. Yassaee, Jingbo Liu, Sergio Verdu

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

New one-shot bounds for multivariate covering are derived via a weighted sum technique and a one-sided concentration inequality which is stronger than the McDiarmid inequality. The new bounds are more compact and sharper than known bounds in the literature. In particular, the covering error can be shown to decay doubly exponentially in the blocklength. Implications for the error exponent in broadcast channels are discussed.

Original language	English (US)
Title of host publication	2017 IEEE International Symposium on Information Theory, ISIT 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	669-673
Number of pages	5
ISBN (Electronic)	9781509040964
DOIs	https://doi.org/10.1109/ISIT.2017.8006612
State	Published - Aug 9 2017
Event	2017 IEEE International Symposium on Information Theory, ISIT 2017 - Aachen, Germany Duration: Jun 25 2017 → Jun 30 2017

Publication series

Name	IEEE International Symposium on Information Theory - Proceedings
ISSN (Print)	2157-8095

Other

Other	2017 IEEE International Symposium on Information Theory, ISIT 2017
Country/Territory	Germany
City	Aachen
Period	6/25/17 → 6/30/17

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Information Systems
Modeling and Simulation
Applied Mathematics

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10.1109/ISIT.2017.8006612

Cite this

Yassaee, M. H., Liu, J., & Verdu, S. (2017). One-shot multivariate covering lemmas via weighted sum and concentration inequalities. In 2017 IEEE International Symposium on Information Theory, ISIT 2017 (pp. 669-673). Article 8006612 (IEEE International Symposium on Information Theory - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIT.2017.8006612

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abstract = "New one-shot bounds for multivariate covering are derived via a weighted sum technique and a one-sided concentration inequality which is stronger than the McDiarmid inequality. The new bounds are more compact and sharper than known bounds in the literature. In particular, the covering error can be shown to decay doubly exponentially in the blocklength. Implications for the error exponent in broadcast channels are discussed.",

author = "Yassaee, {Mohammad H.} and Jingbo Liu and Sergio Verdu",

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Yassaee, MH, Liu, J & Verdu, S 2017, One-shot multivariate covering lemmas via weighted sum and concentration inequalities. in 2017 IEEE International Symposium on Information Theory, ISIT 2017., 8006612, IEEE International Symposium on Information Theory - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 669-673, 2017 IEEE International Symposium on Information Theory, ISIT 2017, Aachen, Germany, 6/25/17. https://doi.org/10.1109/ISIT.2017.8006612

One-shot multivariate covering lemmas via weighted sum and concentration inequalities. / Yassaee, Mohammad H.; Liu, Jingbo; Verdu, Sergio.
2017 IEEE International Symposium on Information Theory, ISIT 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 669-673 8006612 (IEEE International Symposium on Information Theory - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - New one-shot bounds for multivariate covering are derived via a weighted sum technique and a one-sided concentration inequality which is stronger than the McDiarmid inequality. The new bounds are more compact and sharper than known bounds in the literature. In particular, the covering error can be shown to decay doubly exponentially in the blocklength. Implications for the error exponent in broadcast channels are discussed.

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One-shot multivariate covering lemmas via weighted sum and concentration inequalities

Abstract

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