The need of using indefinite kernels in machine learning methods attracted many research interests on indefinite learning in both theory and algorithm.
Jan 1, 2018 · This paper introduces the indefinite learning in the framework of least squares support vector machines (LS-SVM).
Indefinite kernel spectral learning · S. Mehrkanoon, X. Huang, J. Suykens · Published in Pattern Recognition 1 June 2018 · Computer Science, Mathematics.
The use of indefinite kernels has attracted many research interests in recent years due to their flexibility. They do not possess the usual restrictions of ...
The use of indefinite kernels has attracted many research interests in recent years due to their flexibility. They do not possess the usual restrictions of ...
To this end we discuss the application of the Nystr om method to a number of commonly used similarity functions, both positive definite and indefinite (i.e..
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Introducing indefinite kernels in multi-class semi-supervised kernel spectral clustering (MSS-KSC) and kernel spectral clustering (KSC, as a special case of ...
Indefinite kernel spectral learning. https://doi.org/10.1016/j.patcog.2018.01.014 ·. Journal: Pattern Recognition, 2018, p. 144-153. Publisher: Elsevier BV.
Indefinite Kernel Spectral Learning. Author: Mehrkanoon, S. Huang, X ; Suykens, Johan. Keywords: Science & Technology, Technology, Computer Science, Artificial ...
In this paper, we propose a method for support vector machine classification using indefinite kernels. Instead of directly minimizing or stabilizing a ...