An extended Newton-type algorithm for ℓ2-regularized sparse logistic regression and its efficiency for classifying large-scale datasets

Rui Wang 0060, Naihua Xiu, Shenglong Zhou 0001. An extended Newton-type algorithm for ℓ2-regularized sparse logistic regression and its efficiency for classifying large-scale datasets. J. Computational Applied Mathematics, 397:113656, 2021. [doi]

@article{WangXZ21-5,
  title = {An extended Newton-type algorithm for ℓ2-regularized sparse logistic regression and its efficiency for classifying large-scale datasets},
  author = {Rui Wang 0060 and Naihua Xiu and Shenglong Zhou 0001},
  year = {2021},
  doi = {10.1016/j.cam.2021.113656},
  url = {https://doi.org/10.1016/j.cam.2021.113656},
  researchr = {https://researchr.org/publication/WangXZ21-5},
  cites = {0},
  citedby = {0},
  journal = {J. Computational Applied Mathematics},
  volume = {397},
  pages = {113656},
}