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arXiv 0902.2399cs.CCcs.DBcs.DS
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Gap Hamming的多轮通信下界及若干结果

A Multi-Round Communication Lower Bound for Gap Hamming and Some Consequences

Joshua Brody, Amit Chakrabarti

摘要:

间隙汉明距离问题出现在证明数据流模型中的一些关键问题的空间下界的背景下。在这个问题中,Alice和Bob必须决定其$n$位输入串之间的汉明距离是否大(即,至少$n/2 + \sqrt n$)或小(即,最多$n/2 - \sqrt n$);他们不在乎它既不大也不小。问题规范中的这个$Θ(\sqrt n)$间隙对于捕获数据流算法所允许的近似是至关重要的。到目前为止,对于随机通信,这个问题的$Ω(n)$下限仅在单向设置中已知。我们证明了一个$Ω(n)$下界的随机协议,使用任何常数轮数。因此,我们得出结论,例如,$ε$ -近似计算数据流中不同元素的数量需要$Ω(1/ε^2)$空间,即使在输入流上多次(恒定数量)通过。这扩展了早期的一次通过下限,回答了一个长期存在的开放问题。我们得到类似的结果,近似的频率矩和近似的经验熵的数据流。在这个过程中,我们还得到了紧的$n - Θ(\sqrt{n}\log n)$上下限的单向确定性通信复杂性的问题。最后,我们给出了单向随机通信复杂性的一个$Ω(n)$下界的简单组合证明。

英文摘要:

The Gap-Hamming-Distance problem arose in the context of proving space lower bounds for a number of key problems in the data stream model. In this problem, Alice and Bob have to decide whether the Hamming distance between their $n$-bit input strings is large (i.e., at least $n/2 + \sqrt n$) or small (i.e., at most $n/2 - \sqrt n$); they do not care if it is neither large nor small. This $Θ(\sqrt n)$ gap in the problem specification is crucial for capturing the approximation allowed to a data stream algorithm. Thus far, for randomized communication, an $Ω(n)$ lower bound on this problem was known only in the one-way setting. We prove an $Ω(n)$ lower bound for randomized protocols that use any constant number of rounds. As a consequence we conclude, for instance, that $ε$-approximately counting the number of distinct elements in a data stream requires $Ω(1/ε^2)$ space, even with multiple (a constant number of) passes over the input stream. This extends earlier one-pass lower bounds, answering a long-standing open question. We obtain similar results for approximating the frequency moments and for approximating the empirical entropy of a data stream. In the process, we also obtain tight $n - Θ(\sqrt{n}\log n)$ lower and upper bounds on the one-way deterministic communication complexity of the problem. Finally, we give a simple combinatorial proof of an $Ω(n)$ lower bound on the one-way randomized communication complexity.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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