Least squares twin support vector machines for pattern classification
By M. A. Kumar, M. Gopal. Expert systems with applications, 2009
619 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Control and Systems Engineering
View Paper: https://www.semanticscholar.org/paper/dd46de744cd1529190471c18a9e1d3cf45a7842f
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In Artificial Intelligence
In Computer Vision and Pattern Recognition
In Control and Systems Engineering
Citations in the corpus
- TSVR: An efficient Twin Support Vector Machine for regression (2010, methodology): “TSVM has become one of the popular methods in machine learning because of its low computational complexity; see e.g. Ghorai, Mukherjee, and Dutta (2009) and Kumar and Gopal (2008, 2009).”
- Improvements on Twin Support Vector Machines (2011, methodology): “In order to compare the behavior of our linear TBSVM with the linear TWSVM and linear SVC, the results of numerical experiments are summarized in Table I, where is selected according to [8], [11].”
- Robust twin support vector machine for pattern classification (2013, methodology): “Some extensions to the TWSVM can be found in [15–18].”