Towards an Algebraic Network Information Theory: Distributed Lossy Computation of Linear Functions

DC Field Value Language
dc.contributor.author Lim, S.H. -
dc.contributor.author Feng, C. -
dc.contributor.author Pastore, A. -
dc.contributor.author Nazer, B. -
dc.contributor.author Gastpar, M. -
dc.date.accessioned 2020-07-15T07:50:55Z -
dc.date.available 2020-07-15T07:50:55Z -
dc.date.created 2020-06-04 -
dc.date.issued 2019-07-12 -
dc.identifier.issn 2157-8095 -
dc.identifier.uri https://sciwatch.kiost.ac.kr/handle/2020.kiost/22551 -
dc.description.abstract Consider the important special case of the K-user distributed source coding problem where the decoder only wishes to recover one or more linear combinations of the sources. The work of Körner and Marton demonstrated that, in some cases, the optimal rate region is attained by random linear codes, and strictly improves upon the best-known achievable rate region established via random i.i.d. codes. Recent efforts have sought to develop a framework for characterizing the achievable rate region for nested linear codes via joint typicality encoding and decoding. Here, we make further progress along this direction by proposing an achievable rate region for simultaneous joint typicality decoding of nested linear codes. Our approach generalizes the results of Körner and Marton to computing an arbitrary number of linear combinations and to the lossy computation setting. © 2019 IEEE. -
dc.description.uri 1 -
dc.language English -
dc.publisher Institute of Electrical and Electronics Engineers Inc. -
dc.relation.isPartOf IEEE International Symposium on Information Theory - Proceedings Volume 2019 -
dc.title Towards an Algebraic Network Information Theory: Distributed Lossy Computation of Linear Functions -
dc.type Conference -
dc.citation.conferenceDate 2019-07-07 -
dc.citation.conferencePlace FR -
dc.citation.endPage 1831 -
dc.citation.startPage 1827 -
dc.citation.title 2019 IEEE International Symposium on Information Theory -
dc.contributor.alternativeName 임성훈 -
dc.identifier.bibliographicCitation 2019 IEEE International Symposium on Information Theory, pp.1827 - 1831 -
dc.identifier.scopusid 2-s2.0-85073171095 -
dc.description.journalClass 1 -
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