Milena J. Petrović, Milica Ivanović, Marijana Ðorðević
{"title":"几种加速和混合加速梯度模型的性能对比分析","authors":"Milena J. Petrović, Milica Ivanović, Marijana Ðorðević","doi":"10.5937/UNIVTHO9-18174","DOIUrl":null,"url":null,"abstract":"We analyze a performance profile of several accelerated and hybrid accelerated methods. All comparative methods are at least linearly convergent and have satisfied numerical characteristics regarding tested metrics: number of iterations, CPU time and number of function evaluations. Among the chosen set of methods we numerically show which one is the most efficient and the most effective. Therewith, we derived a conclusion about what type of method is more preferable to use considering analyzed metrics.","PeriodicalId":22896,"journal":{"name":"The University Thought - Publication in Natural Sciences","volume":"39 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Comparative performance analysis of some accelerated and hybrid accelerated gradient models\",\"authors\":\"Milena J. Petrović, Milica Ivanović, Marijana Ðorðević\",\"doi\":\"10.5937/UNIVTHO9-18174\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We analyze a performance profile of several accelerated and hybrid accelerated methods. All comparative methods are at least linearly convergent and have satisfied numerical characteristics regarding tested metrics: number of iterations, CPU time and number of function evaluations. Among the chosen set of methods we numerically show which one is the most efficient and the most effective. Therewith, we derived a conclusion about what type of method is more preferable to use considering analyzed metrics.\",\"PeriodicalId\":22896,\"journal\":{\"name\":\"The University Thought - Publication in Natural Sciences\",\"volume\":\"39 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The University Thought - Publication in Natural Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5937/UNIVTHO9-18174\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The University Thought - Publication in Natural Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5937/UNIVTHO9-18174","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comparative performance analysis of some accelerated and hybrid accelerated gradient models
We analyze a performance profile of several accelerated and hybrid accelerated methods. All comparative methods are at least linearly convergent and have satisfied numerical characteristics regarding tested metrics: number of iterations, CPU time and number of function evaluations. Among the chosen set of methods we numerically show which one is the most efficient and the most effective. Therewith, we derived a conclusion about what type of method is more preferable to use considering analyzed metrics.
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