A Unified Framework for Problems on Guessing, Source Coding, and Tasks Partitioning

Thakre, AshishKumar, Ashisha;

Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/10880

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DC Field	Value	Language
dc.contributor.author	Thakre, AshishKumar, Ashisha;	en_US
dc.date.accessioned	2022-11-03T19:46:23Z	-
dc.date.available	2022-11-03T19:46:23Z	-
dc.date.issued	2022	-
dc.identifier.citation	Kumar, M. A., Sunny, A., Thakre, A., Kumar, A., & Manohar, G. D. (2022). A unified framework for problems on guessing, source coding, and tasks partitioning. Paper presented at the IEEE International Symposium on Information Theory - Proceedings, , 2022-June 3339-3344. doi:10.1109/ISIT50566.2022.9834851 Retrieved from www.scopus.com	en_US
dc.identifier.isbn	978-1665421591	-
dc.identifier.issn	2157-8095	-
dc.identifier.other	EID(2-s2.0-85136254847)	-
dc.identifier.uri	https://doi.org/10.1109/ISIT50566.2022.9834851	-
dc.identifier.uri	https://dspace.iiti.ac.in/handle/123456789/10880	-
dc.description.abstract	We formulate a general framework for which Campbell's source coding, Arikan's guessing, Huleihel et al.'s memorryless guessing, Bunte and Lapidoth's tasks partitioning problems are specific ones. We then use this framework to show an equivalence among these problems. © 2022 IEEE.	en_US
dc.language.iso	en	en_US
dc.publisher	Institute of Electrical and Electronics Engineers Inc.	en_US
dc.source	IEEE International Symposium on Information Theory - Proceedings	en_US
dc.subject	Campbell; Partitioning problem; Source-coding; Task partitioning; Unified framework	en_US
dc.title	A Unified Framework for Problems on Guessing, Source Coding, and Tasks Partitioning	en_US
dc.type	Conference Paper	en_US
Appears in Collections:	Department of Electrical Engineering

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