PCA (4 papers)
H. Abdi, L. Williams, "Principal component analysis", Wiley Interdisciplinary Reviews Computational Statistics, Volume 2, pages 433-459, 2010.
J. Shlens, “A tutorial on principal component analysis", Preprint, 2014.
M. Greenacre, P. Groenen, T. Hastie, A. d’Enza, A. Markos, E. Tuzhilina, “Principal component analysis", Nature Reviews Methods Primers, Volume 2, No. 1, page 100, 2022.
L. Smallman, A. Artemiou, “A Literature Review of Sparse Exponential Family PCA”, Journal of Statistical Theory and Practice, February 2022.
Subspace Tracking (6 papers)
J. Delmas , "Subspace tracking for signal processing", Adaptive Signal Processing: Next Generation Solutions, Wiley-IEEE Press, pages 211-270, 2010.
C. Wang, Y. Eldar, Y. Lu, “Subspace Estimation from Incomplete Observations: A High-Dimensional Analysis” , IEEE Journal of Selected Topics in Signal Processing, December 2018.
A. Marchioni, L. Prono, M. Mangia, F. Pareschi, R. Rovatti, G. Setti “Streaming Algorithms for Subspace Analysis: an Edge- and Hardware-oriented review”, May 2021
L. Thanh, N. Dung, N. Trung, K. Abed-Meraim, "A brief survey on robust subspace tracking algorithms in signal processingA brief survey on robust subspace tracking algorithms in signal processing", Journal on Electronics and Communications, Volume 11, No. 1, pages 16-25, January 2021.
N. Dung, N. Trung, K. Abed-Meraim, "Robust subspace tracking algorithms in signal processing: A brief survey”, REV Journal on Electronics and Communications, 2021.
L. Thanh, K. Abed-Meraim, N. Linh-Trung, "A Contemporary and Comprehensive Survey on Streaming Tensor Decomposition", Preprint, October 2023.
Classical RPCA (11 papers)
S. Engelen, M. Hubert, K. Vanden Branden, “A Comparison of Three Procedures for Robust PCA in High Dimensions”, Austrian Journal of Statistics, Volume 34, No. 2, pages 117-126, 2005.
R. Wilcox, "Robust principal components: A generalized variance perspective", Behavior Research Methods, Volume 40, Issue 1, pages 102-108, 2008.
C. Pascoal, M. Oliveira, A. Pacheco, R. Valadas, "Detection of outliers using robust principal component analysis: A simulation study", Soft Computing and Statistical Methods in Data Analysis", pages 499-507, 2010.
S. Sapra, "Robust vs. classical principal component analysis in the presence of outliers", Applied Economics Letters, Volume 17, No.6, 519-523, 2010.
E. Kotwa, "Robust procedures in chemometrics", PhD Thesis, DTU, Kongens Lyngby, Denmark, 2012.
B. De Ketelaere, M. Hubert, E. Schmitt, “Overview of PCA-based statistical process monitoring methods for time-dependent, high-dimensional data”, Journal of Quality Technology, 47, Volume 318–335, 2015.
S. Brodinova, T. Ortner, P. Filzmoser, M. Zaharieva, C. Breiteneder, "Evaluation of robust PCA for supervised audio outlier detection", Technical Report CS-2015-2, 2015.
D. Hong, L. Balzano, J. Fessler, “Towards a Theoretical Analysis of PCA for Heteroscedastic Data", Allerton Conference on Communication, Control, and Computing, Allerton 2016, pages 496–503, 2016.
V. Goryainov, E. Goryainova, "Comparison of the Quality of Robust PCA versions in the Reducion of datasets with Outliers", IEEE International Conference Management of large-scale system development, MLSD 2023, pages 1-5, Moscow, Russian Federation, 2023.
N. Zakaria, W. Syahidah, W. Yusoff, N. Muhammad, “A comparative study of classical and robust principal component analysis in historical multivariate data”, AIP Conferences, March 2024.
Y. Liu, L. Shu, Y. Li, G. Tian, “A Comparison of Robust Principal Component Analysis in High Dimensions”, Communications in Statistics, Simulation and Computation, pages 1-17, 2025.
Robust PCA via L+ S Decomposition (7 papers)
N. Vaswani, P. Narayanamurthy, "Static and Dynamic Robust PCA and Matrix Completion: A Review", Proceedings of IEEE, July 2018.
T. Bouwmans, S. Javed, H. Zhang, Z. Lin, R. Otazo, “On the Applications of Robust PCA in Image and Video Processing”, Special Issue on "Rethinking PCA for Modern Datasets: Theory, Algorithms, and Applications”, Proceedings of IEEE, July 2018.
N. Vaswani, T. Bouwmans, S. Javed, P. Narayanamurthy, “Robust Subspace Learning: Robust PCA, Robust Subspace Tracking and Robust Subspace Recovery”, IEEE Signal Processing Magazine, Volume 35, No. 4, pages 32-55, July 2018.
N. Vaswani, T. Bouwmans, S. Javed, P. Narayanamurthy, “Robust PCA and Robust Subspace Tracking: A Comparative Evaluation”, IEEE Statistical Signal Processing Workshop, SSP 2018, Freiburg, Germany, June 2018.
T. Bouwmans, A. Sobral, S. Javed, S. Jung, E. Zahzah, "Decomposition into Low-rank plus Additive Matrices for Background/Foreground Separation: A Review for a Comparative Evaluation with a Large-Scale Dataset", Computer Science Review, Volume 23, pages 1-71, February 2017.
T. Bouwmans, N. Aybat, E. Zahzah, Handbook on "Robust Low-Rank and Sparse Matrix Decomposition: Applications in Image and Video Processing", CRC Press, Taylor and Francis Group, May 2016.
T. Bouwmans, E. Zahzah, “Robust PCA via Principal Component Pursuit: A Review for a Comparative Evaluation in Video Surveillance”, Special Issue on Background Models Challenge, Computer Vision and Image Understanding, CVIU 2014, Volume 122, pages 22–34, May 2014.