A parallel SVM training algorithm on large-scale classification problems

  title={A parallel SVM training algorithm on large-scale classification problems},
  author={Jian-pei Zhang and Zhong-Wei Li and Jing Yang},
  journal={2005 International Conference on Machine Learning and Cybernetics},
  pages={1637-1641 Vol. 3}
Support vector machine (SVM) has become a popular classification tool but the main disadvantages of SVM algorithms are their large memory requirement and computation time to deal with very large datasets. To speed up the process of training SVM, parallel methods have been proposed by splitting the problem into smaller subsets and training a network to assign samples of different subsets. A parallel training algorithm on large-scale classification problems is proposed, in which multiple SVM… CONTINUE READING
Highly Cited
This paper has 98 citations. REVIEW CITATIONS

From This Paper

Figures, tables, and topics from this paper.


Publications citing this paper.
Showing 1-10 of 40 extracted citations

A Support Vector Machine training Algorithm based on Cascade Structure

First International Conference on Innovative Computing, Information and Control - Volume I (ICICIC'06) • 2006
View 5 Excerpts
Method Support
Highly Influenced

Parallel Computing of Support Vector Machines: A Survey

ACM Comput. Surv. • 2019
View 8 Excerpts
Highly Influenced

A method of pre-sentence text based on Map/Reduce storage and indexing classification

2014 IEEE 5th International Conference on Software Engineering and Service Science • 2014
View 4 Excerpts
Highly Influenced

HDSVM: A High Efficiency Distributed SVM Framework over Data Stream

2017 IEEE International Symposium on Parallel and Distributed Processing with Applications and 2017 IEEE International Conference on Ubiquitous Computing and Communications (ISPA/IUCC) • 2017
View 1 Excerpt

A convergent and fully distributable SVMs training algorithm

2016 International Joint Conference on Neural Networks (IJCNN) • 2016
View 1 Excerpt

BPPGD: Budgeted Parallel Primal Gradient Descent Kernel SVM on Spark

2016 IEEE First International Conference on Data Science in Cyberspace (DSC) • 2016
View 1 Excerpt

99 Citations

Citations per Year
Semantic Scholar estimates that this publication has 99 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.
Showing 1-10 of 11 references

Comparison of parallel and cascade methods for training support vector machines on large-scale problems

Proceedings of 2004 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.04EX826) • 2004
View 3 Excerpts

Y.Bengio, S.Bengio, “A parallel mixture of SVMs for very large scale problems

R. Collobert
Neural Information Processing Systems, • 2004
View 1 Excerpt

Parallelization of the incremental proximal support vector machine classifier using a heap-based tree topology

A. Tveit, H. Engum
Tech. Report, IDI, NTNU, Trondheim • 2003
View 2 Excerpts

SVMTorch : support vector machines for large - scale regression problems ”

S. Bengio
Parallel computing • 2003