{"title":"代数复杂性理论与矩阵乘法","authors":"F. Gall","doi":"10.1145/2608628.2627493","DOIUrl":null,"url":null,"abstract":"This tutorial will give an overview of algebraic complexity theory focused on bilinear complexity, and describe several powerful techniques to analyze the complexity of computational problems from linear algebra, in particular matrix multiplication. The presentation of these techniques will follow the history of progress on constructing asymptotically fast algorithms for matrix multiplication, and include its most recent developments.","PeriodicalId":243282,"journal":{"name":"International Symposium on Symbolic and Algebraic Computation","volume":"26 6‐7","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"949","resultStr":"{\"title\":\"Algebraic complexity theory and matrix multiplication\",\"authors\":\"F. Gall\",\"doi\":\"10.1145/2608628.2627493\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This tutorial will give an overview of algebraic complexity theory focused on bilinear complexity, and describe several powerful techniques to analyze the complexity of computational problems from linear algebra, in particular matrix multiplication. The presentation of these techniques will follow the history of progress on constructing asymptotically fast algorithms for matrix multiplication, and include its most recent developments.\",\"PeriodicalId\":243282,\"journal\":{\"name\":\"International Symposium on Symbolic and Algebraic Computation\",\"volume\":\"26 6‐7\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-01-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"949\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Symposium on Symbolic and Algebraic Computation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2608628.2627493\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Symposium on Symbolic and Algebraic Computation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2608628.2627493","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Algebraic complexity theory and matrix multiplication
This tutorial will give an overview of algebraic complexity theory focused on bilinear complexity, and describe several powerful techniques to analyze the complexity of computational problems from linear algebra, in particular matrix multiplication. The presentation of these techniques will follow the history of progress on constructing asymptotically fast algorithms for matrix multiplication, and include its most recent developments.
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