Ramp loss K-Support Vector Classification-Regression; a robust and sparse multi-class approach to the intrusion detection problem

Seyed Mojtaba Hosseini Bamakan, Huadong Wang, Yong Shi. Ramp loss K-Support Vector Classification-Regression; a robust and sparse multi-class approach to the intrusion detection problem. Knowl.-Based Syst., 126:113-126, 2017. [doi]

@article{BamakanWS17,
  title = {Ramp loss K-Support Vector Classification-Regression; a robust and sparse multi-class approach to the intrusion detection problem},
  author = {Seyed Mojtaba Hosseini Bamakan and Huadong Wang and Yong Shi},
  year = {2017},
  doi = {10.1016/j.knosys.2017.03.012},
  url = {https://doi.org/10.1016/j.knosys.2017.03.012},
  researchr = {https://researchr.org/publication/BamakanWS17},
  cites = {0},
  citedby = {0},
  journal = {Knowl.-Based Syst.},
  volume = {126},
  pages = {113-126},
}