LDA (1 paper)
R. Fisher, "The Use of Multiple Measurements in Taxonomic Problems", Annals of Eugenics, Volume 7, Issue 2, pages 179–188, 1936.
Online LDA (1 paper)
G. Demir, K. Ozmehmet, "Online Local Learning Algorithms for Linear Discriminant Analysis", Pattern Recognition Letters, Volume 26 , No. 4, pages 421–431, 2005.
Incremental LDA (2 papers)
D. Chen, L. Zhang, "An Incremental Linear Discriminant Analysis using Fixed Point Method", pages 1334-1339, 2006.
T. Kim,S. Wong, B. Stenger, J. Kittler, R. Cipolla, "Incremental Linear Discriminant Analysis using Sufficient Spanning Set Approximations", IEEE International Conference on Computer Vision and Pattern Recognition, CVPR 2007, pages 1-8, June 2007.
Fast LDA (1 paper)
F. Tang, H. Tao, "Fast Linear discriminant analysis using binary base", International Conference on Pattern Recognition, ICPR 2006, 2006.
Orthogonal LDA (OLDA) (1 paper)
J. Ye, T. Xiong, "Null space versus orthogonal linear discriminant analysis", International Conference on Machine Learning, ICML 2006, pages 1073-1080, 2006
Uncorrelated LDA (ULDA) (1 paper)
J. Ye, R. Janardan, Q. Li, H. Park, "Feature reduction via generalized uncorrelated linear discriminant analysis", IEEE Transactions on Knowledge Data Engeneering, 2006.
Sparse LDA (SLDA) (2 papers)
Z. Qiao, L. Zhou, J. Huang , "Sparse linear discriminant analysis with applications to high dimensional low sample size data", IAENG International Journal of Applied Mathematics, Volume 39, No. 1, 2009.
Y. Wang, C. Wang, B. Jiang, "Sr-LDA:Sparse and Reduced-Rank Linear Discriminant Analysis for High Dimensional Matrix", IEEE Signal Processing Letters, Volume 31, pages 1134-1138, 2024.
Multi-view LDA (1 paper)
M. Kan, S. Shan, H. Zhang, S. Lao, X. Chen, "Multi-view discriminant analysis", European Conference on Computer Vision, ECCV 2012, pages 808–821, 2012.
Polynomial LDA (1 paper)
R. Ran, T. Wang, Z. Li, B. Fang, “Polynomial Linear Discriminant Analysis”, The Journal of Supercomputing, Volume 80, pages 413-434, 2024.
Regularized LDA (1 paper)
M. Mahadi, T. Ballal, M. Moinuddin, T. Naffouri, U. Saggaf, "Regularized Linear Discriminant Analysis using a Nonlinear Covariance Matrix Estimator", IEEE Transactions on Signal Processing, Volume 72, pages 1049-1064, 2024.
Robust LDA (1 paper)
S. Aerts, I. Wilms, "Cellwise robust regularized discriminant analysis", Statistical Analysis and Data Mining, Volume 10, No. 6, pages 436-447, 2017.
Robust Sparse LDA (3 papers)
RSLDA
J. Wen, X. Fang, J. Cui, L. Fei, K. Yan, Y. Chen, Y. Xu, "Robust sparse linear discriminant analysis", IEEE Transactions on Circuits Systems and Video Technology, Volume 29, No. 2, pages 390-403, 2019.
RSLDA-IIKC
S. Li, H. Zhang, R. Ma, J. Zhou, J. Wen, B. Zhang, "Linear discriminant analysis with generalized kernel constraint for robust image classification", Pattern Recognition, Volume136, 2023.
RSLDA+
J. Liu, M. Feng, X. Xiu, W. Liu,“Towards robust and sparse linear discriminant analysis for image classification”, Pattern Recognition, April 2024.
LDA-L1 (10 papers)
X. Li, W. Hu, H. Wang, Z. Zhang, ‘‘Linear discriminant analysis using rotational invariant L1 norm", Neurocomputing, Volume 73, pages 2571-2579, 2010.
F. Zhong, J. Zhang, ‘‘Linear discriminant analysis based on L1- norm maximization,’’ IEEE Transactions on Image Processing, pages 3018-3027, 2013.
H. Wang, X. Lu, Z. Hu, W. Zheng, ‘‘Fisher discriminant analysis with L1-norm", IEEE Transactions on Cybernetics, 2014.
W. Zheng, Z. Lin, H. Wang, ‘‘L1-norm kernel discriminant analysis via Bayes error bound optimization for robust feature extraction", IEEE Transactions on Neural Networks and Learning Systems, 2014.
Y. Liu, Q. Gao, S. Miao, X. Gao, F. Nie, Y. Li, ‘‘A non-greedy algorithm for L1-norm LDA", IEEE Transactions on Image Processing, Volume 26, No. 2, pp. 684–695, 2017.
Q. Ye, J. Yang, F. Liu, C. Zhao, N. Ye, T. Yin, ‘‘L1-norm distance linear discriminant analysis based on an effective iterative algorithm", IEEE Transactions on Circuits Systems and Video Technology, Volume 28, No. 1, pages 114–129, 2018.
C. Li, Z. Zheng, M. Liu, Y. Shao, W. Chen, ‘‘Robust recursive absolute value inequalities discriminant analysis with sparseness,’’ Neural Netw., vol. 93, pp. 205–218, Sep. 2017.
C. Li, Y. Shao, Z. Wang, N. Deng, Z. Yang, ‘‘Robust Bhattacharyya bound linear discriminant analysis through an adaptive algorithm", Knowledeg based Systems, Volume 183, 2019.
C. Li, Y. Shao, W. Yin, M. Liu, ‘‘Robust and sparse linear discriminant analysis via an alternating direction method of multipliers", IEEE Transactions on Neural Networks and Learning Systems, Volume 31, No. 3, pages 915-926, March 2020.
D. Zhang, Y. Sun, Q. Ye, J. Tang, ‘‘Recursive discriminative subspace learning with ℓ1-norm distance constraint,’’ IEEE Transactions on Cybernetics, Volume 50, No. 5, pages 2138–2151, May 2020.
Lp LDA (3 papers)
H. Oh, N. Kwak, ‘‘Generalization of linear discriminant analysis using Lp-norm", Pattern Recognition Letters, Volume 34, No. 6, pages 679-685, 2013.
Q. Ye, L. Fu, Z. Zhang, H. Zhao, M. Naiem, ‘‘Lp- and Ls-norm distance based robust linear discriminant analysis", Neural Networks, Volume 105, pages 393-404, 2018.
C. Li, Y. Shao, Z. Wang, N. Deng, ‘‘Robust bilateral Lp-norm two-dimensional linear discriminant analysis", Information Sciences, Volume 500, pages 274–297, 2019.
L2,1LDA-ADMM (1 paper)
C. Li, Y. Li, Y. Meng, P. Ren, Y. Shao, "l2,1-Norm Regularized Robust and Sparse Linear Discriminant Analysis via an Alternating Direction Method of Multipliers", IEEE Access, Volume 11, pages 34250-34259, 2023.
Latent LDA (1 paper)
LLDA-ISL
J. Zhou, Q. Zhang, S. Zeng, B. Zhang, L. Fang “Latent Linear Discriminant Analysis for feature extraction via Isometric Structural Learning”, Pattern Recognition, Volume 149, May 2024.
Adaptive Local LDA (ALLDA) (1 paper)
F. Nie, Z. Wang, R. Wang, Z. Wang, X. Li, "Adaptive local linear discriminant analysis", ACM Transactions on Knowledge Discovery Data, Volume 14, No. 1, pages 1-19, 2020.
Adaptive Fuzzy LDA (AFLDA) (1 paper)
J. Wang, H. Yin, F. Nie, X. Li, “Adaptive and fuzzy locality discriminant analysis for dimensionality reduction”, Pattern Recognition, Volume 151, July 2024.