Robust multicategory support matrix machines

We consider the classification problem when the input features are represented as matrices rather than vectors. To preserve the intrinsic structures for classification, a successful method is the support matrix machine (SMM) in Luo et al. (in: Proceedings of the 32nd international conference on mach...

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Vydáno v:	Mathematical programming Ročník 176; číslo 1-2; s. 429 - 463
Hlavní autoři:	Qian, Chengde, Tran-Dinh, Quoc, Fu, Sheng, Zou, Changliang, Liu, Yufeng
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Berlin/Heidelberg Springer Berlin Heidelberg 01.07.2019 Springer Nature B.V
Témata:	Algorithms Calculus of Variations and Optimal Control; Optimization Classification Classifiers Combinatorics Full Length Paper Iterative methods Linear operators Machine learning Mathematical analysis Mathematical and Computational Physics Mathematical Methods in Physics Mathematical models Mathematics Mathematics and Statistics Mathematics of Computing Matrix algebra Matrix methods Numerical Analysis Operators (mathematics) Optimization Outliers (statistics) Robustness (mathematics) Theoretical Fisher consistency Nonconvex optimization Spectral elastic net 90C25 90-08 DCA (difference of convex function) algorithm Robustness Angle-based classifiers DCA (difference of convex function) algorithm
ISSN:	0025-5610, 1436-4646
On-line přístup:	Získat plný text
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