{"title":"计算帮助位的信息论内容价值","authors":"Salman Beigi, O. Etesami, A. Gohari","doi":"10.1109/IWCIT.2015.7140205","DOIUrl":null,"url":null,"abstract":"“Help bits” are some limited trusted information about an instance or instances of a computational problem that may reduce the computational complexity of solving that instance or instances. Assume that we can efficiently solve k instances of a decision problem using some help bits whose entropy is less than k when the k instances are drawn independently from a particular distribution. Then there is an upper bound on the average-case complexity of the problem, namely we can efficiently solve an instance drawn from that distribution correctly with probability better than 1/2.","PeriodicalId":166939,"journal":{"name":"2015 Iran Workshop on Communication and Information Theory (IWCIT)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The value of information-theoretic content of help bits for computation\",\"authors\":\"Salman Beigi, O. Etesami, A. Gohari\",\"doi\":\"10.1109/IWCIT.2015.7140205\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"“Help bits” are some limited trusted information about an instance or instances of a computational problem that may reduce the computational complexity of solving that instance or instances. Assume that we can efficiently solve k instances of a decision problem using some help bits whose entropy is less than k when the k instances are drawn independently from a particular distribution. Then there is an upper bound on the average-case complexity of the problem, namely we can efficiently solve an instance drawn from that distribution correctly with probability better than 1/2.\",\"PeriodicalId\":166939,\"journal\":{\"name\":\"2015 Iran Workshop on Communication and Information Theory (IWCIT)\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-05-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 Iran Workshop on Communication and Information Theory (IWCIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWCIT.2015.7140205\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Iran Workshop on Communication and Information Theory (IWCIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWCIT.2015.7140205","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The value of information-theoretic content of help bits for computation
“Help bits” are some limited trusted information about an instance or instances of a computational problem that may reduce the computational complexity of solving that instance or instances. Assume that we can efficiently solve k instances of a decision problem using some help bits whose entropy is less than k when the k instances are drawn independently from a particular distribution. Then there is an upper bound on the average-case complexity of the problem, namely we can efficiently solve an instance drawn from that distribution correctly with probability better than 1/2.
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