{"title":"Online Learning with Universal Model and Predictor Classes","authors":"J. Poland","doi":"10.1109/ITW.2006.1633819","DOIUrl":null,"url":null,"abstract":"We review and relate some classical and recent results from the theory of online learning based on discrete classes of models or predictors. Among these frameworks, Bayesian methods, MDL, and prediction (or action) with expert advice are studied. We will discuss ways to work with universal base classes corresponding to sets of all programs on some fixed universal Turing machine, resulting in universal induction schemes.","PeriodicalId":293144,"journal":{"name":"2006 IEEE Information Theory Workshop - ITW '06 Punta del Este","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 IEEE Information Theory Workshop - ITW '06 Punta del Este","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITW.2006.1633819","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
We review and relate some classical and recent results from the theory of online learning based on discrete classes of models or predictors. Among these frameworks, Bayesian methods, MDL, and prediction (or action) with expert advice are studied. We will discuss ways to work with universal base classes corresponding to sets of all programs on some fixed universal Turing machine, resulting in universal induction schemes.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
