{"title":"关于贝叶斯风险下界的元界","authors":"Shota Saito","doi":"10.1109/ISIT50566.2022.9834810","DOIUrl":null,"url":null,"abstract":"For the problem of parameter estimation in a Bayesian setting, information-theoretic lower bounds of the Bayes risk have been investigated. Previous studies have proven the lower bound of the Bayes risk in a different manner and characterized the lower bound via different quantities such as the mutual information, Sibson’s α-mutual information, and Csiszár’s f-informativity. In this paper, we introduce an inequality called a \"meta-bound for lower bounds of the Bayes risk\" and show that the previous results can be derived from this bound.","PeriodicalId":348168,"journal":{"name":"2022 IEEE International Symposium on Information Theory (ISIT)","volume":"2016 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"On Meta-Bound for Lower Bounds of Bayes Risk\",\"authors\":\"Shota Saito\",\"doi\":\"10.1109/ISIT50566.2022.9834810\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For the problem of parameter estimation in a Bayesian setting, information-theoretic lower bounds of the Bayes risk have been investigated. Previous studies have proven the lower bound of the Bayes risk in a different manner and characterized the lower bound via different quantities such as the mutual information, Sibson’s α-mutual information, and Csiszár’s f-informativity. In this paper, we introduce an inequality called a \\\"meta-bound for lower bounds of the Bayes risk\\\" and show that the previous results can be derived from this bound.\",\"PeriodicalId\":348168,\"journal\":{\"name\":\"2022 IEEE International Symposium on Information Theory (ISIT)\",\"volume\":\"2016 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE International Symposium on Information Theory (ISIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISIT50566.2022.9834810\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Symposium on Information Theory (ISIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISIT50566.2022.9834810","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
For the problem of parameter estimation in a Bayesian setting, information-theoretic lower bounds of the Bayes risk have been investigated. Previous studies have proven the lower bound of the Bayes risk in a different manner and characterized the lower bound via different quantities such as the mutual information, Sibson’s α-mutual information, and Csiszár’s f-informativity. In this paper, we introduce an inequality called a "meta-bound for lower bounds of the Bayes risk" and show that the previous results can be derived from this bound.