DocumentCode :
3681132
Title :
Classification with Extreme Learning Machine on GPU
Author :
Tomá ;Petr Gajdo;Vojtech Uher;Václav Snáel
Author_Institution :
Dept. of Comput. Sci., VSB-Tech. Univ. of Ostrava, Ostrava - Poruba, Czech Republic
fYear :
2015
Firstpage :
116
Lastpage :
122
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.
Keywords :
"Graphics processing units","Neurons","Training","Support vector machines","Matrix decomposition","Neural networks","Algorithm design and analysis"
Publisher :
ieee
Conference_Titel :
Intelligent Networking and Collaborative Systems (INCOS), 2015 International Conference on
Type :
conf
DOI :
10.1109/INCoS.2015.30
Filename :
7312059
Link To Document :
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