{"title":"用热核Pagerank求解具有边界条件的局部线性系统","authors":"F. Graham, O. Simpson","doi":"10.1080/15427951.2015.1009522","DOIUrl":null,"url":null,"abstract":"We present an efficient algorithm for solving local linear systems with a boundary condition using the Green’s function of a connected induced subgraph related to the system. We introduce the method of using the Dirichlet heat kernel pagerank1 vector to approximate local solutions to linear systems in the graph Laplacian, satisfying given boundary conditions over a particular subset of vertices. With an efficient algorithm for approximating Dirichlet heat kernel pagerank, our Local Linear Solver algorithm computes an approximate local solution with multiplicative and additive error ε by performing O(ε−5s3log (s3ε−1)log n) random walk steps, where n is the number of vertices in the full graph, and s is the size of the local system on the induced subgraph.","PeriodicalId":38105,"journal":{"name":"Internet Mathematics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2015-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/15427951.2015.1009522","citationCount":"9","resultStr":"{\"title\":\"Solving Local Linear Systems with Boundary Conditions Using Heat Kernel Pagerank\",\"authors\":\"F. Graham, O. Simpson\",\"doi\":\"10.1080/15427951.2015.1009522\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present an efficient algorithm for solving local linear systems with a boundary condition using the Green’s function of a connected induced subgraph related to the system. We introduce the method of using the Dirichlet heat kernel pagerank1 vector to approximate local solutions to linear systems in the graph Laplacian, satisfying given boundary conditions over a particular subset of vertices. With an efficient algorithm for approximating Dirichlet heat kernel pagerank, our Local Linear Solver algorithm computes an approximate local solution with multiplicative and additive error ε by performing O(ε−5s3log (s3ε−1)log n) random walk steps, where n is the number of vertices in the full graph, and s is the size of the local system on the induced subgraph.\",\"PeriodicalId\":38105,\"journal\":{\"name\":\"Internet Mathematics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-01-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1080/15427951.2015.1009522\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Internet Mathematics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/15427951.2015.1009522\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Mathematics\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Internet Mathematics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/15427951.2015.1009522","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Mathematics","Score":null,"Total":0}
Solving Local Linear Systems with Boundary Conditions Using Heat Kernel Pagerank
We present an efficient algorithm for solving local linear systems with a boundary condition using the Green’s function of a connected induced subgraph related to the system. We introduce the method of using the Dirichlet heat kernel pagerank1 vector to approximate local solutions to linear systems in the graph Laplacian, satisfying given boundary conditions over a particular subset of vertices. With an efficient algorithm for approximating Dirichlet heat kernel pagerank, our Local Linear Solver algorithm computes an approximate local solution with multiplicative and additive error ε by performing O(ε−5s3log (s3ε−1)log n) random walk steps, where n is the number of vertices in the full graph, and s is the size of the local system on the induced subgraph.