Lossy computing of correlated sources with fractional sampling

Xi Liu, Osvaldo Simeone, Elza Erkip

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper considers the problem of lossy compression for the computation of a function of two correlated sources, both of which are observed at the encoder. Due to presence of observation costs, the encoder is allowed to observe only subsets of the samples from both sources, with a fraction of such sample pairs possibly overlapping. For both Gaussian and binary sources, the distortion-rate function, or rate-distortion function, is characterized for selected functions and with quadratic and Hamming distortion metrics, respectively. Based on these results, for both examples, the optimal measurement overlap fraction is shown to depend on the function to be computed by the decoder, on the source correlation and on the link rate. Special cases are discussed in which the optimal overlap fraction is the maximum or minimum possible value given the sampling budget, illustrating non-trivial performance trade-offs in the design of the sampling strategy.

Original languageEnglish (US)
Title of host publication2012 IEEE Information Theory Workshop, ITW 2012
Pages232-236
Number of pages5
DOIs
StatePublished - 2012
Event2012 IEEE Information Theory Workshop, ITW 2012 - Lausanne, Switzerland
Duration: Sep 3 2012Sep 7 2012

Other

Other2012 IEEE Information Theory Workshop, ITW 2012
CountrySwitzerland
CityLausanne
Period9/3/129/7/12

Fingerprint

Sampling
Costs

ASJC Scopus subject areas

  • Information Systems

Cite this

Liu, X., Simeone, O., & Erkip, E. (2012). Lossy computing of correlated sources with fractional sampling. In 2012 IEEE Information Theory Workshop, ITW 2012 (pp. 232-236). [6404665] https://doi.org/10.1109/ITW.2012.6404665

Lossy computing of correlated sources with fractional sampling. / Liu, Xi; Simeone, Osvaldo; Erkip, Elza.

2012 IEEE Information Theory Workshop, ITW 2012. 2012. p. 232-236 6404665.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Liu, X, Simeone, O & Erkip, E 2012, Lossy computing of correlated sources with fractional sampling. in 2012 IEEE Information Theory Workshop, ITW 2012., 6404665, pp. 232-236, 2012 IEEE Information Theory Workshop, ITW 2012, Lausanne, Switzerland, 9/3/12. https://doi.org/10.1109/ITW.2012.6404665
Liu X, Simeone O, Erkip E. Lossy computing of correlated sources with fractional sampling. In 2012 IEEE Information Theory Workshop, ITW 2012. 2012. p. 232-236. 6404665 https://doi.org/10.1109/ITW.2012.6404665
Liu, Xi ; Simeone, Osvaldo ; Erkip, Elza. / Lossy computing of correlated sources with fractional sampling. 2012 IEEE Information Theory Workshop, ITW 2012. 2012. pp. 232-236
@inproceedings{df6bee0ba2af49768bd44a71091a1ddf,
title = "Lossy computing of correlated sources with fractional sampling",
abstract = "This paper considers the problem of lossy compression for the computation of a function of two correlated sources, both of which are observed at the encoder. Due to presence of observation costs, the encoder is allowed to observe only subsets of the samples from both sources, with a fraction of such sample pairs possibly overlapping. For both Gaussian and binary sources, the distortion-rate function, or rate-distortion function, is characterized for selected functions and with quadratic and Hamming distortion metrics, respectively. Based on these results, for both examples, the optimal measurement overlap fraction is shown to depend on the function to be computed by the decoder, on the source correlation and on the link rate. Special cases are discussed in which the optimal overlap fraction is the maximum or minimum possible value given the sampling budget, illustrating non-trivial performance trade-offs in the design of the sampling strategy.",
author = "Xi Liu and Osvaldo Simeone and Elza Erkip",
year = "2012",
doi = "10.1109/ITW.2012.6404665",
language = "English (US)",
isbn = "9781467302234",
pages = "232--236",
booktitle = "2012 IEEE Information Theory Workshop, ITW 2012",

}

TY - GEN

T1 - Lossy computing of correlated sources with fractional sampling

AU - Liu, Xi

AU - Simeone, Osvaldo

AU - Erkip, Elza

PY - 2012

Y1 - 2012

N2 - This paper considers the problem of lossy compression for the computation of a function of two correlated sources, both of which are observed at the encoder. Due to presence of observation costs, the encoder is allowed to observe only subsets of the samples from both sources, with a fraction of such sample pairs possibly overlapping. For both Gaussian and binary sources, the distortion-rate function, or rate-distortion function, is characterized for selected functions and with quadratic and Hamming distortion metrics, respectively. Based on these results, for both examples, the optimal measurement overlap fraction is shown to depend on the function to be computed by the decoder, on the source correlation and on the link rate. Special cases are discussed in which the optimal overlap fraction is the maximum or minimum possible value given the sampling budget, illustrating non-trivial performance trade-offs in the design of the sampling strategy.

AB - This paper considers the problem of lossy compression for the computation of a function of two correlated sources, both of which are observed at the encoder. Due to presence of observation costs, the encoder is allowed to observe only subsets of the samples from both sources, with a fraction of such sample pairs possibly overlapping. For both Gaussian and binary sources, the distortion-rate function, or rate-distortion function, is characterized for selected functions and with quadratic and Hamming distortion metrics, respectively. Based on these results, for both examples, the optimal measurement overlap fraction is shown to depend on the function to be computed by the decoder, on the source correlation and on the link rate. Special cases are discussed in which the optimal overlap fraction is the maximum or minimum possible value given the sampling budget, illustrating non-trivial performance trade-offs in the design of the sampling strategy.

UR - http://www.scopus.com/inward/record.url?scp=84873113981&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84873113981&partnerID=8YFLogxK

U2 - 10.1109/ITW.2012.6404665

DO - 10.1109/ITW.2012.6404665

M3 - Conference contribution

SN - 9781467302234

SP - 232

EP - 236

BT - 2012 IEEE Information Theory Workshop, ITW 2012

ER -