{"title":"基于GPU的极限学习机分类","authors":"Toma Jeowicz, P. Gajdoš, Vojtěch Uher, V. Snás̃el","doi":"10.1109/INCoS.2015.30","DOIUrl":null,"url":null,"abstract":"The general classification is a machine learning task that tries to assign the best class to a given unknown input vector based on past observations (training data). Most of developed algorithms are very time consuming for large datasets (Support Vector Machine, Deep Neural Networks, etc.). Extreme Learning Machine (ELM) is a high quality classification algorithm that gains much popularity in recent years. This paper shows that the speed of learning of this algorithm may be improved by using GPU platform. Experimental results showed that proposed approach is much faster and provides the same accuracy as the original ELM algorithm. The proposed approach runs completely on GPU platform and thus it may be effectively incorporated within other applications.","PeriodicalId":345650,"journal":{"name":"2015 International Conference on Intelligent Networking and Collaborative Systems","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Classification with Extreme Learning Machine on GPU\",\"authors\":\"Toma Jeowicz, P. Gajdoš, Vojtěch Uher, V. Snás̃el\",\"doi\":\"10.1109/INCoS.2015.30\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The general classification is a machine learning task that tries to assign the best class to a given unknown input vector based on past observations (training data). Most of developed algorithms are very time consuming for large datasets (Support Vector Machine, Deep Neural Networks, etc.). Extreme Learning Machine (ELM) is a high quality classification algorithm that gains much popularity in recent years. This paper shows that the speed of learning of this algorithm may be improved by using GPU platform. Experimental results showed that proposed approach is much faster and provides the same accuracy as the original ELM algorithm. The proposed approach runs completely on GPU platform and thus it may be effectively incorporated within other applications.\",\"PeriodicalId\":345650,\"journal\":{\"name\":\"2015 International Conference on Intelligent Networking and Collaborative Systems\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-09-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on Intelligent Networking and Collaborative Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INCoS.2015.30\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Intelligent Networking and Collaborative Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INCoS.2015.30","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Classification with Extreme Learning Machine on GPU
The general classification is a machine learning task that tries to assign the best class to a given unknown input vector based on past observations (training data). Most of developed algorithms are very time consuming for large datasets (Support Vector Machine, Deep Neural Networks, etc.). Extreme Learning Machine (ELM) is a high quality classification algorithm that gains much popularity in recent years. This paper shows that the speed of learning of this algorithm may be improved by using GPU platform. Experimental results showed that proposed approach is much faster and provides the same accuracy as the original ELM algorithm. The proposed approach runs completely on GPU platform and thus it may be effectively incorporated within other applications.