{"title":"概率递归理论与隐式计算复杂性","authors":"Ugo Dal Lago, Sara Zuppiroli, M. Gabbrielli","doi":"10.7561/SACS.2014.2.177","DOIUrl":null,"url":null,"abstract":"We show that probabilistic computable functions, i.e., those functions outputting distributions and computed by probabilistic Turing machines, can be characterized by a natural generalization of Church and Kleene’s partial recursive functions. The obtained algebra, following Leivant, can be restricted so as to capture the notion of polytime sampleable distributions, a key concept in average-case complexity and cryptography.","PeriodicalId":53862,"journal":{"name":"Scientific Annals of Computer Science","volume":"1 1","pages":"97-114"},"PeriodicalIF":0.5000,"publicationDate":"2014-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Probabilistic Recursion Theory and Implicit Computational Complexity\",\"authors\":\"Ugo Dal Lago, Sara Zuppiroli, M. Gabbrielli\",\"doi\":\"10.7561/SACS.2014.2.177\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We show that probabilistic computable functions, i.e., those functions outputting distributions and computed by probabilistic Turing machines, can be characterized by a natural generalization of Church and Kleene’s partial recursive functions. The obtained algebra, following Leivant, can be restricted so as to capture the notion of polytime sampleable distributions, a key concept in average-case complexity and cryptography.\",\"PeriodicalId\":53862,\"journal\":{\"name\":\"Scientific Annals of Computer Science\",\"volume\":\"1 1\",\"pages\":\"97-114\"},\"PeriodicalIF\":0.5000,\"publicationDate\":\"2014-09-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Scientific Annals of Computer Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.7561/SACS.2014.2.177\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, THEORY & METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific Annals of Computer Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.7561/SACS.2014.2.177","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
Probabilistic Recursion Theory and Implicit Computational Complexity
We show that probabilistic computable functions, i.e., those functions outputting distributions and computed by probabilistic Turing machines, can be characterized by a natural generalization of Church and Kleene’s partial recursive functions. The obtained algebra, following Leivant, can be restricted so as to capture the notion of polytime sampleable distributions, a key concept in average-case complexity and cryptography.
期刊介绍:
Scientific Annals of Computer Science is an international journal devoted to papers in computer science with results which are formally stated and proved. It is mainly a forum for the dissemination of formal solutions of problems appearing in all areas of computer science. We only consider original work which has not been previously published in other journals, nor submitted simultaneously for publication elsewhere. Extended versions of papers which have previously appeared in conference proceedings are also considered; the authors should indicate this at the time of submission. Promoting quality over quantity, Scientific Annals of Computer Science does not consider papers outside the scope of the journal. Starting with volume 17, SACS becomes an open access journal without subscription. All articles are freely available online, offering an increased visibility and usage of their results.