{"title":"关于傅立叶分析和学习理论的三场讲座","authors":"Haonan Zhang","doi":"arxiv-2409.10886","DOIUrl":null,"url":null,"abstract":"Fourier analysis on the discrete hypercubes $\\{-1,1\\}^n$ has found numerous\napplications in learning theory. A recent breakthrough involves the use of a\nclassical result from Fourier analysis, the Bohnenblust--Hille inequality, in\nthe context of learning low-degree Boolean functions. In these lecture notes,\nwe explore this line of research and discuss recent progress in discrete\nquantum systems and classical Fourier analysis.","PeriodicalId":501312,"journal":{"name":"arXiv - MATH - Mathematical Physics","volume":"36 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Three lectures on Fourier analysis and learning theory\",\"authors\":\"Haonan Zhang\",\"doi\":\"arxiv-2409.10886\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Fourier analysis on the discrete hypercubes $\\\\{-1,1\\\\}^n$ has found numerous\\napplications in learning theory. A recent breakthrough involves the use of a\\nclassical result from Fourier analysis, the Bohnenblust--Hille inequality, in\\nthe context of learning low-degree Boolean functions. In these lecture notes,\\nwe explore this line of research and discuss recent progress in discrete\\nquantum systems and classical Fourier analysis.\",\"PeriodicalId\":501312,\"journal\":{\"name\":\"arXiv - MATH - Mathematical Physics\",\"volume\":\"36 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - MATH - Mathematical Physics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2409.10886\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - MATH - Mathematical Physics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.10886","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Three lectures on Fourier analysis and learning theory
Fourier analysis on the discrete hypercubes $\{-1,1\}^n$ has found numerous
applications in learning theory. A recent breakthrough involves the use of a
classical result from Fourier analysis, the Bohnenblust--Hille inequality, in
the context of learning low-degree Boolean functions. In these lecture notes,
we explore this line of research and discuss recent progress in discrete
quantum systems and classical Fourier analysis.