TY - GEN
T1 - Hypergraph-based Coding Schemes for Two Source Coding Problems under Maximal Distortion
AU - Basu, Sourya
AU - Seo, Daewon
AU - Varshney, Lav R.
N1 - Funding Information:
This work was funded in part by the IBM-Illinois Center for Cognitive Computing Systems Research (C3SR), a research collaboration as part of the IBM AI Horizons Network.
Publisher Copyright:
© 2020 IEEE.
PY - 2020/6
Y1 - 2020/6
N2 - We consider two problems in multiterminal source coding under maximal distortion: distributed coding for computing and successive refinement. In distributed coding for computing, we propose a hypergraph-based coding scheme which matches the sum-rate bound of the Berger-Tung inner bound. Further, this scheme matches the entire Berger-Tung inner region when the sources are independent and it outperforms existing graph-based coding schemes. For successive refinement, we propose a hypergraph-based scheme that attains the entire rate region.
AB - We consider two problems in multiterminal source coding under maximal distortion: distributed coding for computing and successive refinement. In distributed coding for computing, we propose a hypergraph-based coding scheme which matches the sum-rate bound of the Berger-Tung inner bound. Further, this scheme matches the entire Berger-Tung inner region when the sources are independent and it outperforms existing graph-based coding schemes. For successive refinement, we propose a hypergraph-based scheme that attains the entire rate region.
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U2 - 10.1109/ISIT44484.2020.9174396
DO - 10.1109/ISIT44484.2020.9174396
M3 - Conference contribution
AN - SCOPUS:85090414914
T3 - IEEE International Symposium on Information Theory - Proceedings
SP - 2426
EP - 2431
BT - 2020 IEEE International Symposium on Information Theory, ISIT 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE International Symposium on Information Theory, ISIT 2020
Y2 - 21 July 2020 through 26 July 2020
ER -