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asymptoticpropertiesofdistributedsocialsamplingalgorithm
Liu Qian1; He Xingkang2; Fang Haitao1
2020
Source Publicationsciencechinainformationscience
ISSN1674-733X
Volume63Issue:1
AbstractSocial sampling is a novel randomized message passing protocol inspired by social communication for opinion formation in social networks. In a typical social sampling algorithm, each agent holds a sample from the empirical distribution of social opinions at initial time, and it collaborates with other agents in a distributed manner to estimate the initial empirical distribution by randomly sampling a message from current distribution estimate. In this paper, we focus on analyzing the theoretical properties of the distributed social sampling algorithm over random networks. First, we provide a framework based on stochastic approximation to study the asymptotic properties of the algorithm. Then, under mild conditions, we prove that the estimates of all agents converge to a common random distribution, which is composed of the initial empirical distribution and the accumulation of quantized error. Besides, by tuning algorithm parameters, we prove the strong consistency, namely, the distribution estimates of agents almost surely converge to the initial empirical distribution. Furthermore, the asymptotic normality of estimation error generated by distributed social sample algorithm is addressed. Finally, we provide a numerical simulation to validate the theoretical results of this paper.
Indexed ByCSCD
Language英语
CSCD IDCSCD:6655421
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Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/51275
Collection中国科学院数学与系统科学研究院
Affiliation1.中国科学院数学与系统科学研究院
2.皇家工学院
Recommended Citation
GB/T 7714
Liu Qian,He Xingkang,Fang Haitao. asymptoticpropertiesofdistributedsocialsamplingalgorithm[J]. sciencechinainformationscience,2020,63(1).
APA Liu Qian,He Xingkang,&Fang Haitao.(2020).asymptoticpropertiesofdistributedsocialsamplingalgorithm.sciencechinainformationscience,63(1).
MLA Liu Qian,et al."asymptoticpropertiesofdistributedsocialsamplingalgorithm".sciencechinainformationscience 63.1(2020).
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