The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Training a Support Vector Machine in the Primal
Open accessAbstract
Most literature on support vector machines (SVMs) concentrates on the dual optimization problem. In this letter, we point out that the primal problem can also be solved efficiently for both linear and nonlinear SVMs and that there is no reason for ignoring this possibility. On the contrary, from the primal point of view, new families of algorithms for large-scale SVM training can be investigated.
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Cites
Boyd, S., & Vandenberghe, L. (2004) · doi:10.1017/cbo9780511804441 · Cited by 56,601
The Nature of Statistical Learning Theory
Vapnik, V. N. (1995) · doi:10.1007/978-1-4757-2440-0 · Cited by 39,138
Golub, G. (2012) · doi:10.56021/9781421407944 · Cited by 34,505
RSVM: Reduced Support Vector Machines
Lee, Y.-J., & Mangasarian, O. L. (2001) · Proceedings of the 2001 SIAM International Conference on Data Mining · doi:10.1137/1.9781611972719.13 · Cited by 647
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(2011) · PubMed · Cited by 990
Parikh, D., & Grauman, K. (2011) · 2011 International Conference on Computer Vision · doi:10.1109/iccv.2011.6126281 · Cited by 851
Challenges in representation learning: A report on three machine learning contests
Goodfellow, I. J., Erhan, D., Luc Carrier, P., Courville, A., Mirza, M., Hamner, B., Cukierski, W., Tang, Y., Thaler, D., Lee, D.-H., et al. (2015) · Neural Networks · doi:10.1016/j.neunet.2014.09.005 · Cited by 697
PCCA: A new approach for distance learning from sparse pairwise constraints
Mignon, A., & Jurie, F. (2012) · 2012 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2012.6247987 · Cited by 592
Optimization Techniques for Semi-Supervised Support Vector Machines
Chapelle, O., Sindhwani, V., & Keerthi, S. S. (2008) · MPG.PuRe (Max Planck Society) · doi:10.5555/1390681.1390688 · Cited by 401
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Metadata
- Authors
- Chapelle, O.
- Venue
- Neural Computation
- Publisher
- MIT Press - Journals
- Published
- 2007-05
- Volume
- 19
- Issue
- 5
- Pages
- 1155-1178
- ISSN
- 0899-7667 (ISSN-L)
- 1530-888X
- OpenAlex
- W2147898188
- Cited by
- 780
- References
- 4
- FWCI
- 53.19
- Type
- journal article
- Language
- en
- Open access
- green
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