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