Robust chance-constrained support vector machines with second-order moment information
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DOI: 10.1007/s10479-015-2039-6
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Cited by:
- Anton Kocheturov & Panos M. Pardalos & Athanasia Karakitsiou, 2019. "Massive datasets and machine learning for computational biomedicine: trends and challenges," Annals of Operations Research, Springer, vol. 276(1), pages 5-34, May.
- Byunghoon Kim & Young-Seon Jeong & Myong K. Jeong, 2021. "New multivariate kernel density estimator for uncertain data classification," Annals of Operations Research, Springer, vol. 303(1), pages 413-431, August.
- Lin, Fengming & Fang, Shu-Cherng & Fang, Xiaolei & Gao, Zheming & Luo, Jian, 2024. "A distributionally robust chance-constrained kernel-free quadratic surface support vector machine," European Journal of Operational Research, Elsevier, vol. 316(1), pages 46-60.
- Andrew J. Keith & Darryl K. Ahner, 2021. "A survey of decision making and optimization under uncertainty," Annals of Operations Research, Springer, vol. 300(2), pages 319-353, May.
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Keywords
Support vector machines; Robust chance constraints; Semidefinite programming; Second order cone programming; Second-order moment information; Estimation errors;All these keywords.
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