Locality and similarity preserving embedding for feature selection. Li X, Liu H, Xu Y. X Fang, Y Xu, X Li, Z Fan, H Liu, Y Chen - Neurocomputing, 2014 - Elsevier GSID: lQOVKVJL4QIJ
Dual graph regularized compact feature representation for unsupervised feature selection. Liu X, Tang C. S Li, C Tang, X Liu, Y Liu, J Chen - Neurocomputing, 2019 - Elsevier GSID: E5UQbDtQIpkJ
Feature selection based on structured sparsity: A comprehensive study. Gui J, Ji S, Sun Z, Tan T, Tao D. J Gui, Z Sun, S Ji, D Tao, T Tan - IEEE transactions on neural …, 2016 - ieeexplore.ieee.org GSID: k5PsfpkLfhIJ
Semisupervised feature selection based on relevance and redundancy criteria. He H, Tang B, Xu J. J Xu, B Tang, H He, H Man - IEEE transactions on neural …, 2016 - ieeexplore.ieee.org GSID: tDUgE-OSpO8J
KernelADASYN: Kernel based adaptive synthetic data generation for imbalanced learning. He H, Tang B. B Tang, H He - 2015 IEEE congress on evolutionary …, 2015 - ieeexplore.ieee.org GSID: eOD_ucAusoIJ
