{"title":"2021年ACM PODS Alberto O. Mendelzon时间测试奖","authors":"A. Bonifati, R. Pagh, T. Schwentick","doi":"10.1145/3452021.3452909","DOIUrl":null,"url":null,"abstract":"The ACM PODS Alberto O. Mendelzon Test-of-Time Award is awarded every year to a paper or a small number of papers published in the PODS proceedings ten years prior that had the most impact in terms of research, methodology, or transfer to practice over the intervening decade. The PODS Executive Committee has appointed us to serve as the Award Committee for 2021. After careful consideration and having solicited external nominations and advice, we have selected the following paper as the award winner for 2021: Tight bounds for L_p samplers, finding duplicates in streams, and related problems by Hossein Jowhari, Mert Sağlam and Gábor Tardos Citation. This paper addresses a question posed by Cormode et al. in VLDB 2005, namely whether a uniform (or nearly uniform) sample can be maintained in a dynamically changing database, where data items may be inserted and deleted, while using space much smaller than the size of the database. More generally, it considers maintaining an L_p sample, where an element must be sampled with probability proportional to w^p (possibly up to some small relative error), where w is a weight that may change dynamically. In SODA 2010, Monemizadeh and Woodruff showed that it is possible to perform L_p sampling in a stream using polylogarithmic space. The PODS 2011 paper by Jowhari, Sağlam and Tardos essentially closes the problem by presenting algorithms with improved space usage, as well as a matching lower bound showing that it is not possible to asymptotically improve the upper bounds. The paper has had a considerable impact on the design of algorithms in streaming and distributed models of computation, where L_p sampling has become an essential part of the toolbox. The survey \"L_p Samplers and Their Applications\" in ACM Computing Surveys (2019) presents a number of surprising applications, for example in graph algorithms and in randomized numerical linear algebra.","PeriodicalId":405398,"journal":{"name":"Proceedings of the 40th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"2021 ACM PODS Alberto O. Mendelzon Test-of-Time Award\",\"authors\":\"A. Bonifati, R. Pagh, T. Schwentick\",\"doi\":\"10.1145/3452021.3452909\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The ACM PODS Alberto O. Mendelzon Test-of-Time Award is awarded every year to a paper or a small number of papers published in the PODS proceedings ten years prior that had the most impact in terms of research, methodology, or transfer to practice over the intervening decade. The PODS Executive Committee has appointed us to serve as the Award Committee for 2021. After careful consideration and having solicited external nominations and advice, we have selected the following paper as the award winner for 2021: Tight bounds for L_p samplers, finding duplicates in streams, and related problems by Hossein Jowhari, Mert Sağlam and Gábor Tardos Citation. This paper addresses a question posed by Cormode et al. in VLDB 2005, namely whether a uniform (or nearly uniform) sample can be maintained in a dynamically changing database, where data items may be inserted and deleted, while using space much smaller than the size of the database. More generally, it considers maintaining an L_p sample, where an element must be sampled with probability proportional to w^p (possibly up to some small relative error), where w is a weight that may change dynamically. In SODA 2010, Monemizadeh and Woodruff showed that it is possible to perform L_p sampling in a stream using polylogarithmic space. The PODS 2011 paper by Jowhari, Sağlam and Tardos essentially closes the problem by presenting algorithms with improved space usage, as well as a matching lower bound showing that it is not possible to asymptotically improve the upper bounds. The paper has had a considerable impact on the design of algorithms in streaming and distributed models of computation, where L_p sampling has become an essential part of the toolbox. The survey \\\"L_p Samplers and Their Applications\\\" in ACM Computing Surveys (2019) presents a number of surprising applications, for example in graph algorithms and in randomized numerical linear algebra.\",\"PeriodicalId\":405398,\"journal\":{\"name\":\"Proceedings of the 40th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-06-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 40th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3452021.3452909\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 40th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3452021.3452909","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
ACM PODS Alberto O. Mendelzon Test-of-Time奖每年颁发给十年前在PODS会议记录上发表的一篇或少数论文,这些论文在研究、方法或在其间的十年中转化为实践方面具有最大的影响。PODS执行委员会已任命我们担任2021年的奖项委员会。经过仔细考虑并征求外部提名和建议,我们选择以下论文作为2021年的获奖者:L_p采样器的紧密界限,在流中发现重复,以及Hossein Jowhari, Mert Sağlam和Gábor Tardos Citation的相关问题。本文解决了Cormode等人在VLDB 2005中提出的一个问题,即在一个动态变化的数据库中,在数据项可以插入和删除的情况下,是否可以使用比数据库大小小得多的空间来维护一个统一(或近乎统一)的样本。更一般地说,它考虑维护一个L_p样本,其中一个元素必须以与w^p成比例的概率进行采样(可能有一些小的相对误差),其中w是一个可能动态变化的权重。在SODA 2010中,Monemizadeh和Woodruff证明了使用多对数空间在流中执行L_p采样是可能的。Jowhari, Sağlam和Tardos在PODS 2011年发表的论文基本上解决了这个问题,提出了改进空间利用率的算法,以及一个匹配的下界,表明不可能渐近地改进上界。本文对流计算和分布式计算模型的算法设计产生了相当大的影响,其中L_p采样已成为工具箱中必不可少的一部分。《ACM计算调查(2019)》中的调查“L_p采样器及其应用”提出了许多令人惊讶的应用,例如在图算法和随机数值线性代数中。
2021 ACM PODS Alberto O. Mendelzon Test-of-Time Award
The ACM PODS Alberto O. Mendelzon Test-of-Time Award is awarded every year to a paper or a small number of papers published in the PODS proceedings ten years prior that had the most impact in terms of research, methodology, or transfer to practice over the intervening decade. The PODS Executive Committee has appointed us to serve as the Award Committee for 2021. After careful consideration and having solicited external nominations and advice, we have selected the following paper as the award winner for 2021: Tight bounds for L_p samplers, finding duplicates in streams, and related problems by Hossein Jowhari, Mert Sağlam and Gábor Tardos Citation. This paper addresses a question posed by Cormode et al. in VLDB 2005, namely whether a uniform (or nearly uniform) sample can be maintained in a dynamically changing database, where data items may be inserted and deleted, while using space much smaller than the size of the database. More generally, it considers maintaining an L_p sample, where an element must be sampled with probability proportional to w^p (possibly up to some small relative error), where w is a weight that may change dynamically. In SODA 2010, Monemizadeh and Woodruff showed that it is possible to perform L_p sampling in a stream using polylogarithmic space. The PODS 2011 paper by Jowhari, Sağlam and Tardos essentially closes the problem by presenting algorithms with improved space usage, as well as a matching lower bound showing that it is not possible to asymptotically improve the upper bounds. The paper has had a considerable impact on the design of algorithms in streaming and distributed models of computation, where L_p sampling has become an essential part of the toolbox. The survey "L_p Samplers and Their Applications" in ACM Computing Surveys (2019) presents a number of surprising applications, for example in graph algorithms and in randomized numerical linear algebra.