Title :
A parallel training algorithm of support vector machines based on the MTC architecture
Author :
Wang, Lei ; Jia, Huading
Author_Institution :
Sch. of Econ. Inf. Eng., Southwest Univ. of Finance & Econ., Chengdu
Abstract :
For accelerating the training speed of support vector machines (SVM), a novel ldquomulti-trifurcate cascade (MTC)rdquo architecture was proposed in this paper, which held the advantages of fast feedback, high utilization rate of nodes, and more feedback support vectors. Then, a parallel algorithm for training SVM was designed based on the MTC architecture, and it was proven to converge to the optimal solution strictly. The experimental results showed that the proposed algorithm obtained very high speedup and efficiency, and needed significantly less training time than the cascade SVM algorithm.
Keywords :
learning (artificial intelligence); parallel algorithms; support vector machines; vectors; feedback support vector; multi trifurcate cascade architecture; parallel training algorithm; support vector machine; Acceleration; Computer architecture; Concurrent computing; Feedback; Finance; Large-scale systems; Parallel algorithms; Quadratic programming; Support vector machine classification; Support vector machines;
Conference_Titel :
Cybernetics and Intelligent Systems, 2008 IEEE Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-1673-8
Electronic_ISBN :
978-1-4244-1674-5
DOI :
10.1109/ICCIS.2008.4670831
