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arXiv 1902.02304cs.DS
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动力学问题的新的摊销胞腔探测下界

New Amortized Cell-Probe Lower Bounds for Dynamic Problems

Sayan Bhattacharya, Monika Henzinger, Stefan Neumann

摘要:

我们建立在Weinstein和Yu(FOCS'16),Larsen(FOCS'12)和Clifford等人(FOCS'15)的最新论文的基础上,提出了一个通用框架,该框架给出了动态数据结构的更新和查询时间的摊销下限。使用我们的框架,我们提出了两个具体的结果。(1)对于动态多项式求值问题,其中多项式被定义在大小为$n^{1+Ω(1)}$的有限域上并且具有次数$n$,任何动态数据结构必须具有分期更新时间$Ω((\lg n/\lg \lg n)^2)$或分期查询时间$Ω((\lg n/\lg \lg n)^2)$。(2)对于动态在线矩阵向量乘法问题,其中我们得到一个$n \times n$矩阵,其全部是从大小为$n^{Θ(1)}$的有限域中提取的,任何动态数据结构必须具有$Ω((\lg n/\lg \lg n)^2)$的摊销更新时间或$Ω(n \cdot (\lg n/\lg \lg n)^2)$的摊销查询时间。对于这两个问题,Larsen(FOCS'12)和Clifford等人(FOCS'15)给出了相同的下限,但仅适用于最坏情况下的更新和查询时间。我们的边界匹配的最高无条件下限已知的任何动态问题的细胞探针模型。

英文摘要:

We build upon the recent papers by Weinstein and Yu (FOCS'16), Larsen (FOCS'12), and Clifford et al. (FOCS'15) to present a general framework that gives amortized lower bounds on the update and query times of dynamic data structures. Using our framework, we present two concrete results. (1) For the dynamic polynomial evaluation problem, where the polynomial is defined over a finite field of size $n^{1+Ω(1)}$ and has degree $n$, any dynamic data structure must either have an amortized update time of $Ω((\lg n/\lg \lg n)^2)$ or an amortized query time of $Ω((\lg n/\lg \lg n)^2)$. (2) For the dynamic online matrix vector multiplication problem, where we get an $n \times n$ matrix whose entires are drawn from a finite field of size $n^{Θ(1)}$, any dynamic data structure must either have an amortized update time of $Ω((\lg n/\lg \lg n)^2)$ or an amortized query time of $Ω(n \cdot (\lg n/\lg \lg n)^2)$. For these two problems, the previous works by Larsen (FOCS'12) and Clifford et al. (FOCS'15) gave the same lower bounds, but only for worst case update and query times. Our bounds match the highest unconditional lower bounds known till date for any dynamic problem in the cell-probe model.

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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