Pairwise support vector machines and their application to large scale problems

Journal of Machine Learning Research

Volumn 13, Issue , 2012, Pages 2279-2292

  Brunner, Carl ^a   Fischer, Andreas ^a   Luig, Klaus ^b   Thies, Thorsten ^b  

^a DRESDEN UNIVERSITY OF TECHNOLOGY   (Germany)

^b Cognitec Systems GmbH ^*  (Germany)

Author keywords

Interclass generalization; Large scale problems; Pairwise kernels; Pairwise support vector machines

Indexed keywords

CLASSIFICATION RESULTS; EFFICIENT IMPLEMENTATION; INTERCLASS GENERALIZATION; LARGE-SCALE PROBLEM; PAIRWISE CLASSIFICATION; PAIRWISE KERNELS; TRAINING SETS;

ARTIFICIAL INTELLIGENCE; SOFTWARE ENGINEERING;

SUPPORT VECTOR MACHINES;

EID: 84869189040     PISSN: 15324435     EISSN: 15337928     Source Type: Journal    
DOI: None     Document Type: Article

References (24)

1. J. Abernethy, F. Bach, T. Evgeniou, and J.-P. Vert. A new approach to collaborative filtering: Operator estimation with spectral regularization. Journal of Machine Learning Research, 10:803-826, 2009.
2. A. Bar-Hillel and D. Weinshall. Learning distance function by coding similarity. In Z. Ghahramani, editor, Proceedings of the 24th International Conference onMachine Learning (ICML '07), pages 65-72. ACM, 2007.
3. A. Bar-Hillel, T. Hertz, and D. Weinshall. Boosting margin based distance functions for clustering. In C. E. Brodley, editor, In Proceedings of the 21st International Conference on Machine Learning (ICML '04), pages 393-400. ACM, 2004a. (Pubitemid 40290833)
4. A. Bar-Hillel, T. Hertz, and D. Weinshall. Learning distance functions for image retrieval. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '04), volume 2, pages 570-577. IEEE Computer Society Press, 2004b.
5. A. Ben-Hur and W. Stafford Noble. Kernel methods for predicting protein-protein interactions. Bioinformatics, 21(1):38-46, 2005.
6. C. Brunner, A. Fischer, K. Luig, and T. Thies. Pairwise kernels, support vector machines, and the application to large scale problems. Technical Report MATH-NM-04-2011, Institute of Numerical Mathematics, Technische Universität Dresden, October 2011. URL http://www.math.tu-dresden.de/fischer.
7. C.-C. Chang and C.-J. Lin. LIBSVM: A library for support vector machines. ACM Transactions on Intelligent Systems and Technology, 2(3):1-26, 2011. URL http://www.csie.ntu.edu.tw/cjlin/libsvm (August 2011).
8. K. Duan and S. S. Keerthi.Which is the best multiclass SVM method? An empirical study. In N. C. Oza, R. Polikar, J. Kittler, and F. Roli, editors, Proceedings of the 6th International Workshop on Multiple Classifier Systems, pages 278-285. Springer, 2005. (Pubitemid 41422626)
9. M. Gamassi, M. Lazzaroni, M. Misino, V. Piuri, D. Sana, and F. Scotti. Accuracy and performance of biometric systems. In Proceedings of the 21th IEEE Instrumentation and Measurement Technology Conference (IMTC '04), pages 510-515. IEEE, 2004.
10. M. Guillaumin, J. Verbeek, and C. Schmid. Is that you? Metric learning approaches for face identification. In Proceedings of the 12th International Conference on Computer Vision (ICCV '09), pages 498-505, 2009. URL http://lear.inrialpes.fr/pubs/2009/GVS09 (August 2011).
11. S. I. Hill and A. Doucet. A framework for kernel-based multi-category classification. Journal of Artificial Intelligence Research, 30(1):525-564, 2007.
12. C.-W. Hsu and C.-J. Lin. A comparison of methods for multiclass support vector machines. IEEE Transactions on Neural Networks, 13(2):415-425, 2002. (Pubitemid 34475042)
13. G. B. Huang, M. Ramesh, T. Berg, and E. Learned-Miller. Labeled faces in the wild: A database for studying face recognition in unconstrained environments. Technical Report 07-49, University of Massachusetts, Amherst, October 2007. URL http://vis-www.cs.umass.edu/lfw/(August 2011).
14. P. Li, Y. Fu, U.Mohammed, J. H. Elder, and S. J. D. Prince. Probabilistic models for inference about identity. IEEE Transactions on Pattern Analysis and Machine Intelligence, 34:144-157, 2012.
15. T. Ojala, M. Pietikäinen, and T. Mäenpää. Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. In IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(7):971-987, 2002. URL http://www.cse.oulu.fi/MVG/Downloads/ LBPMatlab (August 2011). (Pubitemid 34835471)
16. P. J. Phillips. Support vector machines applied to face recognition. In M. S. Kearns, S. A. Solla, and D. A. Cohn, editors, Advances in Neural Information Processing Systems 11, pages 803-809. MIT Press, 1999.
17. J. C. Platt. Fast training of support vector machines using sequential minimal optimization. In B. Schölkopf, C. J. C. Burges, and A. J. Smola, editors, Advances in Kernel Methods: Support Vector Learning, pages 185-208. MIT Press, 1999.
18. R. Rifkin and A. Klautau. In defense of one-vs-all classification. Journal of Machine Learning Research, 5:101-141, 2004.
19. B. Schölkopf and A. J. Smola. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. MIT Press, 2001.
20. B. Schölkopf, J. C. Platt, J. Shawe-Taylor, A. J. Smola, and R. C.Williamson. Estimating the support of a high-dimensional distribution. Neural Computations, 13(7):1443-1471, 2001. (Pubitemid 33595028)
21. J. P. Vert, J. Qiu, andW. Noble. A new pairwise kernel for biological network inference with support vector machines. BMC Bioinformatics, 8(Suppl 10):S8, 2007.
22. L. Wei, Y. Yang, R. M. Nishikawa, and M. N. Wernick. Learning of perceptual similarity from expert readers for mammogram retrieval. In Proceedings of the IEEE International Symposium on Biomedical Imaging (ISBI), pages 1356-1359. IEEE, 2006. (Pubitemid 44732578)
23. L. Wolf, T. Hassner, and Y. Taigman. Descriptor based methods in the wild. In Faces in Real-Life Images Workshop at the European Conference on Computer Vision (ECCV '08), 2008. URL http://www.openu.ac.il/home/hassner/ projects/Patchlbp (August 2011).
24. L. Wolf, T. Hassner, and Y. Taigman. Similarity scores based on background samples. In Proceedings of the 9th Asian Conference on Computer Vision (ACCV '09), volume 2, pages 88-97, 2009.