Distributed Signal Detection under Communication Constraints

Distributed Signal Detection under Communication Constraints
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通信约束下的分布式信号检测

DOI:
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发表时间:
2020
期刊:
Annual Conference Computational Learning Theory
影响因子:
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通讯作者:
Himanshu Tyagi
Himanshu Tyagi
中科院分区:
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文献类型:
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作者:
Jayadev Acharya;C. Canonne;Himanshu Tyagi

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来自$d$维球形高斯分布的独立绘制分布在用户之间,每个用户持有一个样本。一个中央服务器试图区分两个假设:分布的平均值为零,或者平均值至少有一个预先指定的阈值。但是,每个用户最多只能向服务器发送$ell$比特。这是在白色噪声中检测信号的经典问题的分布式变体。 我们研究这个分布式测试问题,并没有一个共同的随机性共享的用户。我们设计的方案有没有这样的共享随机性。然后,我们得到了下界的协议与公共随机性,这是紧时,$ell=O(1)$。最后,我们总结了几个问题和开放的问题。
Independent draws from a $d$-dimensional spherical Gaussian distribution are distributed across users, each holding one sample. A central server seeks to distinguish between the two hypotheses: the distribution has zero mean, or the mean has $ell_2$-norm at least $varepsilon$, a pre-specified threshold. However, the users can each transmit at most $ell$ bits to the server. This is a distributed variant of the classic problem of detecting signal in white noise. We study this distributed testing problem with and without the availability of a common randomness shared by the users. We design schemes with and without such shared randomness. We then obtain lower bounds for protocols with public randomness, which are tight when $ell=O(1)$. We finally conclude with several conjectures and open problems.
DOI: --
发表时间: 2019
期刊: and Programming
影响因子: --
作者:
Andoni, Alexandr;Malkin, Tal;Nosatzki, Negev Shekel
通讯作者: Nosatzki, Negev Shekel
DOI: 10.5555/3458064.3458085
发表时间: 2021
期刊: Proceedings of the 32th Annual ACM-SIAM Symposium on Discrete Algorithms
影响因子: --
作者:
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DOI: 10.1109/tit.2020.3028440
发表时间: 2018-12
影响因子: 2.5
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通讯作者: Jayadev Acharya;C. Canonne;Himanshu Tyagi
DOI: --
发表时间: 2020
期刊: Advances in Neural Information Processing Systems
影响因子: --
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