{"title":"熵空间的一种随机局部搜索算法分析","authors":"Sultan Alam, Satyajit Thakor, Syed Abbas","doi":"10.1109/ISCON47742.2019.9036317","DOIUrl":null,"url":null,"abstract":"In previous work, we proposed a randomized local search algorithm to determine the distribution associated with a vector given in the entropy space. The algorithm also finds the nearest vector and corresponding distribution if the given vector is non-entropic. The utility of the algorithm for entropy optimization has been shown. A trade-off between entropy functions is observed. The convergence is better in comparison to the other algorithms used in the entropy region. Finally, the time and space complexities have been computed.","PeriodicalId":124412,"journal":{"name":"2019 4th International Conference on Information Systems and Computer Networks (ISCON)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Analysis of a Randomized Local Search Algorithm for the Entropy Space\",\"authors\":\"Sultan Alam, Satyajit Thakor, Syed Abbas\",\"doi\":\"10.1109/ISCON47742.2019.9036317\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In previous work, we proposed a randomized local search algorithm to determine the distribution associated with a vector given in the entropy space. The algorithm also finds the nearest vector and corresponding distribution if the given vector is non-entropic. The utility of the algorithm for entropy optimization has been shown. A trade-off between entropy functions is observed. The convergence is better in comparison to the other algorithms used in the entropy region. Finally, the time and space complexities have been computed.\",\"PeriodicalId\":124412,\"journal\":{\"name\":\"2019 4th International Conference on Information Systems and Computer Networks (ISCON)\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 4th International Conference on Information Systems and Computer Networks (ISCON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISCON47742.2019.9036317\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 4th International Conference on Information Systems and Computer Networks (ISCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCON47742.2019.9036317","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Analysis of a Randomized Local Search Algorithm for the Entropy Space
In previous work, we proposed a randomized local search algorithm to determine the distribution associated with a vector given in the entropy space. The algorithm also finds the nearest vector and corresponding distribution if the given vector is non-entropic. The utility of the algorithm for entropy optimization has been shown. A trade-off between entropy functions is observed. The convergence is better in comparison to the other algorithms used in the entropy region. Finally, the time and space complexities have been computed.