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Beyond the cut-set bound: Uncertainty computations in network coding with correlated sources
, Article IEEE International Symposium on Information Theory - Proceedings, 31 July 2011 through 5 August 2011 ; July , 2011 , Pages 598-602 ; 21578104 (ISSN) ; 9781457705953 (ISBN) ; Yang, S ; Jaggi, S ; Sharif University of Technology
2011
Abstract
Cut-set bounds on achievable rates for network communication protocols are not in general tight. In this paper we introduce a new technique for proving converses for the problem of transmission of correlated sources in networks, that results in bounds that are tighter than the corresponding cut-set bounds. We also define the concept of "uncertainty region" which might be of independent interest. We provide a full characterization of this region for the case of two correlated random variables. The bounding technique works as follows: on one hand we show that if the communication problem is solvable, the uncertainty of certain random variables in the network with respect to imaginary parties...
Blind index coding
, Article IEEE Transactions on Information Theory ; Volume 63, Issue 4 , 2017 , Pages 2076-2097 ; 00189448 (ISSN) ; Maddah Ali, M. A ; Avestimehr, A. S ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2017
Abstract
We introduce the blind index coding (BIC) problem, in which a single sender communicates distinct messages to multiple users over a shared channel. Each user has partial knowledge of each message as side information. However, unlike classical index coding, in BIC, the sender is uncertain of what side information is available to each user. In particular, the sender only knows the amount of bits in each user's side information but not its content. This problem can arise naturally in caching and wireless networks. In order to blindly exploit side information in the BIC problem, we develop a hybrid coding scheme that XORs uncoded bits of a subset of messages with random combinations of bits from...
A novel granular approach for detecting dynamic online communities in social network
, Article Soft Computing ; 2018 ; 14327643 (ISSN) ; Zakerolhosseini, A ; Bagheri Shouraki, S ; Homayounvala, E ; Sharif University of Technology
Springer Verlag
2018
Abstract
The great surge in the research of community discovery in complex network is going on due to its challenging aspects. Dynamicity and overlapping nature are among the common characteristics of these networks which are the main focus of this paper. In this research, we attempt to approximate the granular human-inspired viewpoints of the networks. This is especially helpful when making decisions with partial knowledge. In line with the principle of granular computing, in which precision is avoided, we define the micro- and macrogranules in two levels of nodes and communities, respectively. The proposed algorithm takes microgranules as input and outputs meaningful communities in rough...
A novel granular approach for detecting dynamic online communities in social network
, Article Soft Computing ; Volume 23, Issue 20 , 2019 , Pages 10339-10360 ; 14327643 (ISSN) ; Zakerolhosseini, A ; Bagheri Shouraki, S ; Homayounvala, E ; Sharif University of Technology
Springer Verlag
2019
Abstract
The great surge in the research of community discovery in complex network is going on due to its challenging aspects. Dynamicity and overlapping nature are among the common characteristics of these networks which are the main focus of this paper. In this research, we attempt to approximate the granular human-inspired viewpoints of the networks. This is especially helpful when making decisions with partial knowledge. In line with the principle of granular computing, in which precision is avoided, we define the micro- and macrogranules in two levels of nodes and communities, respectively. The proposed algorithm takes microgranules as input and outputs meaningful communities in rough...