Lune

KDD2023顶会

SketchPolymer: Estimate Per-item Tail Quantile Using One Sketch

Jiarui Guo, Yisen Hong, Yuhan Wu, Yunfei Liu, Tong Yang, Bin Cui

2023年份
13被引次数
5顶会引用

摘要

1 Estimating the quantile of distribution, especially tail distribution, is an interesting topic in data stream models, and has obtained extensive interest from many researchers. In this paper, we propose a novel sketch, namely SketchPolymer to accurately estimate per-item tail quantile. SketchPolymer uses a technique called Early Filtration to filter infrequent items, and another technique called VSS to reduce error. Our experimental results show that the accuracy of SketchPolymer is on average 32.67 times better than state-of-the-art techniques. We also implement our SketchPolymer on P4 and FPGA platforms to verify its deployment flexibility. All our codes are available at GitHub [1].

问问这篇 Paper

智能体会读完全文。

Lune 把这篇 Paper 索引到了最后一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。

可以从这些问题问起

智能体调用

Luneget_paper_fulltext

在 Lune 里问

免费开始,无需绑卡

lune papers fulltext 08d9c283-fa67-47c0-be0e-a30b537b5c6e

引用它的顶会 Paper5

问问它们各自怎么用它

它引用的顶会 Paper4

相关 Paper

黄昏的海面,两侧是细线勾勒的悬崖