Kernel-based online machine learning and support vector reduction

@article{Agarwal2007KernelbasedOM,
  title={Kernel-based online machine learning and support vector reduction},
  author={Sumeet Agarwal and V. Vijaya Saradhi and Harish Karnick},
  journal={Neurocomputing},
  year={2007},
  volume={71},
  pages={1230-1237}
}
We apply kernel-based machine learning methods to online learning situations, and look at the related requirement of reducing the complexity of the learnt classifier. Online methods are particularly useful in situations which involve streaming data, such as medical or financial applications. We show that the concept of span of support vectors can be used to build a classifier that performs reasonably well while satisfying given space and time constraints, thus making it potentially suitable for… CONTINUE READING

From This Paper

Figures, tables, and topics from this paper.

Citations

Publications citing this paper.
Showing 1-10 of 18 extracted citations

A Fast Algorithm of Convex Hull Vertices Selection for Online Classification

IEEE Transactions on Neural Networks and Learning Systems • 2018
View 4 Excerpts
Highly Influenced

Support Vector Number Reduction: Survey and Experimental Evaluations

IEEE Transactions on Intelligent Transportation Systems • 2014
View 4 Excerpts
Highly Influenced

Kernel Association for Classification and Prediction: A Survey

IEEE Transactions on Neural Networks and Learning Systems • 2015
View 2 Excerpts

References

Publications referenced by this paper.
Showing 1-10 of 20 references

Bounds on Error Expectation for Support Vector Machines

Neural Computation • 2000
View 4 Excerpts
Highly Influenced

Sparseness of Support Vector Machines

Journal of Machine Learning Research • 2003
View 3 Excerpts
Highly Influenced

Kernel - based online machine learning and support vector reduction

V. Vijaya Saradhi Sumeet Agarwal
2007

Support vector machines on a budget

Tom Downs, Kevin E. Gates
Advances in Neural Information Processing Systems • 2006

Benchmark repository. Technical report, Intelligent Data Analysis Group, Fraunhofer-FIRST

G. Rätsch
2005
View 1 Excerpt

Mangasarian . Rsvm : reduced support vector machines

L. O.
IEEE Transactions on Signal Processing • 2004

Similar Papers

Loading similar papers…