{"title":"来自阿贝尔群的Cayley图的硬度量","authors":"I. Newman, Y. Rabinovich","doi":"10.4086/toc.2009.v005a006","DOIUrl":null,"url":null,"abstract":"Hard metrics are the class of extremal metrics with respect to embedding into Euclidean Spaces: their distortion is as bad as it possibly gets, which is Ω(log n). Besides being very interesting objects akin to expanders and good codes, with rich structure of independent interest, such metrics are important for obtaining lower bounds in Combinatorial Optimization, e.g., on the value of MinCut/MaxFlow ratio for multicommodity flows. \n \nFor more than a decade, a single family of hard metrics was known (see [10,3]). Recently, a different such family was found (see [8]), causing a certain excitement among the researchers in the area. \n \nIn this paper we present another construction of hard metrics, different from [10,3], and more general yet clearer and simpler than [8]. Our results naturally extend to NEG and to l1.","PeriodicalId":55992,"journal":{"name":"Theory of Computing","volume":"42 1","pages":"157-162"},"PeriodicalIF":0.7000,"publicationDate":"2007-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Hard Metrics from Cayley Graphs of Abelian Groups\",\"authors\":\"I. Newman, Y. Rabinovich\",\"doi\":\"10.4086/toc.2009.v005a006\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Hard metrics are the class of extremal metrics with respect to embedding into Euclidean Spaces: their distortion is as bad as it possibly gets, which is Ω(log n). Besides being very interesting objects akin to expanders and good codes, with rich structure of independent interest, such metrics are important for obtaining lower bounds in Combinatorial Optimization, e.g., on the value of MinCut/MaxFlow ratio for multicommodity flows. \\n \\nFor more than a decade, a single family of hard metrics was known (see [10,3]). Recently, a different such family was found (see [8]), causing a certain excitement among the researchers in the area. \\n \\nIn this paper we present another construction of hard metrics, different from [10,3], and more general yet clearer and simpler than [8]. Our results naturally extend to NEG and to l1.\",\"PeriodicalId\":55992,\"journal\":{\"name\":\"Theory of Computing\",\"volume\":\"42 1\",\"pages\":\"157-162\"},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2007-02-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Theory of Computing\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.4086/toc.2009.v005a006\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, THEORY & METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Theory of Computing","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.4086/toc.2009.v005a006","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
Hard metrics are the class of extremal metrics with respect to embedding into Euclidean Spaces: their distortion is as bad as it possibly gets, which is Ω(log n). Besides being very interesting objects akin to expanders and good codes, with rich structure of independent interest, such metrics are important for obtaining lower bounds in Combinatorial Optimization, e.g., on the value of MinCut/MaxFlow ratio for multicommodity flows.
For more than a decade, a single family of hard metrics was known (see [10,3]). Recently, a different such family was found (see [8]), causing a certain excitement among the researchers in the area.
In this paper we present another construction of hard metrics, different from [10,3], and more general yet clearer and simpler than [8]. Our results naturally extend to NEG and to l1.
期刊介绍:
"Theory of Computing" (ToC) is an online journal dedicated to the widest dissemination, free of charge, of research papers in theoretical computer science.
The journal does not differ from the best existing periodicals in its commitment to and method of peer review to ensure the highest quality. The scientific content of ToC is guaranteed by a world-class editorial board.