Siyun Zhang, Jian-wei Liu, Xin Zuo, X. Wan, M. Kamel
{"title":"MRAC-MU在线学习","authors":"Siyun Zhang, Jian-wei Liu, Xin Zuo, X. Wan, M. Kamel","doi":"10.1109/ICARCV.2018.8581389","DOIUrl":null,"url":null,"abstract":"In this paper, we apply the method of control theory to machine learning, proposing a new multiplication update algorithm combined with adaptive control theory, we name it MRAC-MU algorithm. A new parameter updating law is obtained according to Lyapunov stability theorem. Using the same object function as the exponential gradient (EG) algorithm, which is the key online learning method to multiplicative updates algorithm, Experiments are used to validate the proposed algorithm has a better result than EG algorithm in prediction accuracy.","PeriodicalId":395380,"journal":{"name":"2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"MRAC-MU Online Learning\",\"authors\":\"Siyun Zhang, Jian-wei Liu, Xin Zuo, X. Wan, M. Kamel\",\"doi\":\"10.1109/ICARCV.2018.8581389\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we apply the method of control theory to machine learning, proposing a new multiplication update algorithm combined with adaptive control theory, we name it MRAC-MU algorithm. A new parameter updating law is obtained according to Lyapunov stability theorem. Using the same object function as the exponential gradient (EG) algorithm, which is the key online learning method to multiplicative updates algorithm, Experiments are used to validate the proposed algorithm has a better result than EG algorithm in prediction accuracy.\",\"PeriodicalId\":395380,\"journal\":{\"name\":\"2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV)\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICARCV.2018.8581389\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICARCV.2018.8581389","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper, we apply the method of control theory to machine learning, proposing a new multiplication update algorithm combined with adaptive control theory, we name it MRAC-MU algorithm. A new parameter updating law is obtained according to Lyapunov stability theorem. Using the same object function as the exponential gradient (EG) algorithm, which is the key online learning method to multiplicative updates algorithm, Experiments are used to validate the proposed algorithm has a better result than EG algorithm in prediction accuracy.