{"title":"Consistency in a model for distributed learning with specialists","authors":"Joel B. Predd, S. Kulkarni, H. Poor","doi":"10.1109/ISIT.2004.1365502","DOIUrl":null,"url":null,"abstract":"Motivated by sensor networks and traditional methods of statistical pattern recognition, a model for distributed learning is formulated. The model is in line with learning models considered in the context of Stone-type classifiers, but differs in the dependency structure of the sampling process; questions of universal consistency are addressed.","PeriodicalId":269907,"journal":{"name":"International Symposium onInformation Theory, 2004. ISIT 2004. Proceedings.","volume":"376 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Symposium onInformation Theory, 2004. ISIT 2004. Proceedings.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISIT.2004.1365502","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Motivated by sensor networks and traditional methods of statistical pattern recognition, a model for distributed learning is formulated. The model is in line with learning models considered in the context of Stone-type classifiers, but differs in the dependency structure of the sampling process; questions of universal consistency are addressed.
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
