The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
Support vector machines
Abstract
Support vector machines (SVMs) are a family of machine learning methods, originally introduced for the problem of classification and later generalized to various other situations. They are based on principles of statistical learning theory and convex optimization, and are currently used in various domains of application, including bioinformatics, text categorization, and computer vision. Copyright © 2009 John Wiley & Sons, Inc. This article is categorized under: Statistical Learning and Exploratory Methods of the Data Sciences > Clustering and Classification
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Cites
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The Nature of Statistical Learning Theory
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A training algorithm for optimal margin classifiers
Boser, B. E., Guyon, I. M., & Vapnik, V. N. (1992) · Proceedings of the fifth annual workshop on Computational learning theory · doi:10.1145/130385.130401 · Cited by 11,992
Text categorization with Support Vector Machines: Learning with many relevant features
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Self-citationPractical methods of optimization
(1988) · Mathematics and Computers in Simulation · doi:10.1016/0378-4754(88)90129-2 · Cited by 5,818
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Schölkopf, B., Burges, C. J. C., & Smola, A. J. (1999) · doi:10.5555/299094 · Cited by 5,789
An Introduction to Support Vector Machines
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Chou, K.-C., & Cai, Y.-D. (2002) · Journal of Biological Chemistry · doi:10.1074/jbc.m204161200 · Cited by 483
Sun, W., Zheng, Y., Yang, K., Zhang, Q., Shah, A. A., Wu, Z., Sun, Y., Feng, L., Chen, D., Xiao, Z., et al. (2019) · Science Advances · doi:10.1126/sciadv.aay4275 · Cited by 344
Support vector machines for predicting membrane protein types by using functional domain composition
Cai, Y.-D., Zhou, G.-P., & Chou, K.-C. (2003) · Biophysical Journal · doi:10.1016/s0006-3495(03)70050-2 · Cited by 284
Theory of deep convolutional neural networks: Downsampling
Zhou, D.-X. (2020) · Neural Networks · doi:10.1016/j.neunet.2020.01.018 · Cited by 263
Real-time fMRI brain computer interfaces: Self-regulation of single brain regions to networks
Ruiz, S., Buyukturkoglu, K., Rana, M., Birbaumer, N., & Sitaram, R. (2014) · Biological Psychology · doi:10.1016/j.biopsycho.2013.04.010 · Cited by 187
Metadata
- Authors
- Mammone, A., Turchi, M., & Cristianini, N.
- Venue
- WIREs Computational Statistics
- Publisher
- Wiley
- Published
- 2009-11
- Volume
- 1
- Issue
- 3
- Pages
- 283-289
- ISSN
- 1939-0068 (ISSN-L)
- 1939-5108
- OpenAlex
- W2012908927
- Cited by
- 699
- References
- 18
- FWCI
- 28.19
- Type
- journal article
- Language
- en
- Open access
- closed
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