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Incremental learning with support vector machines
Abstract
Support vector machines (SVMs) have become a popular tool for machine learning with large amounts of high dimensional data. In this paper an approach for incremental learning with support vector machines is presented, that improves the existing approach of Syed et al. (1999). An insight into the interpretability of support vectors is also given.
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Cited by
Learning a Unified Classifier Incrementally via Rebalancing
Hou, S., Pan, X., Loy, C. C., Wang, Z., & Lin, D. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.00092 · Cited by 1,195
End-to-End Incremental Learning
Castro, F. M., Marín-Jiménez, M. J., Guil, N., Schmid, C., & Alahari, K. (2018) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-01258-8_15 · Cited by 1,184
Cross-domain video concept detection using adaptive svms
Yang, J., Yan, R., & Hauptmann, A. G. (2007) · Proceedings of the 15th ACM international conference on Multimedia · doi:10.1145/1291233.1291276 · Cited by 667
Learning drifting concepts: Example selection vs. example weighting
Klinkenberg, R. (2004) · Intelligent Data Analysis · doi:10.3233/ida-2004-8305 · Cited by 438
Classifying large data sets using SVMs with hierarchical clusters
Yu, H., Yang, J., & Han, J. (2003) · Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining · doi:10.1145/956750.956786 · Cited by 273
Metadata
- Authors
- Ruping, S.
- Venue
- Proceedings 2001 IEEE International Conference on Data Mining
- Publisher
- IEEE Comput. Soc
- Published
- 2002-11-14
- Pages
- 641-642
- ISSN
- 1550-4786 (ISSN-L)
- OpenAlex
- W2132641846
- Cited by
- 524
- References
- 0
- FWCI
- 14.14
- Type
- conference paper
- Language
- en
- Open access
- closed
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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
