{"title":"Elastic Consistency","authors":"Dan Alistarh, I. Markov, Giorgi Nadiradze","doi":"10.1145/3544979.3544991","DOIUrl":null,"url":null,"abstract":"Machine learning models can match or surpass humans on specialized tasks such as image classification [20, 14], speech recognition [37], or complex games [39]. One key tool behind this progress has been a family of optimization methods which fall under the umbrella term of stochastic gradient descent (SGD) [35], which are by and large the method of choice for training large-scale machine learning models.","PeriodicalId":387985,"journal":{"name":"ACM SIGACT News","volume":"428 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM SIGACT News","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3544979.3544991","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Machine learning models can match or surpass humans on specialized tasks such as image classification [20, 14], speech recognition [37], or complex games [39]. One key tool behind this progress has been a family of optimization methods which fall under the umbrella term of stochastic gradient descent (SGD) [35], which are by and large the method of choice for training large-scale machine learning models.