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Coordination via Shared Randomness

机译:通过共享随机性进行协调

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We study a distributed sampling problem where a set of processors want to output correlated sequences of random variables with the help of a coordinator which has access to several independent sources of randomness. Each processor has access to a subset of these sources. When these subsets are pairwise disjoint (individually shared randomness model), we characterize the rate of communication required from the coordinator to the processors over a multicast link. We also give an upper bound on the communication rate for the randomness-on-the-forehead model where each processor observes all but one source of randomness. For the general model, we completely characterize the trade-off region between communication and shared randomness rates when all the processors wish to output the same random sequence.
机译:我们研究了分布式采样问题,其中一组处理器希望借助可访问多个独立随机性源的协调器来输出相关的随机变量序列。每个处理器都可以访问这些源的子集。当这些子集成对不相交时(每个人共享随机性模型),我们将表征从协调器到多播链路上从处理器到处理器的通信速率。我们还为头上随机性模型提供了通信速率的上限,在该模型中,每个处理器都观察到除了一个随机性源以外的所有随机性。对于一般模型,当所有处理器希望输出相同的随机序列时,我们将完全刻画通信与共享随机率之间的权衡区域。

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