[43] Zihang Meng, Rudrasis Chakraborty, and Vikas Singh. An online riemannian pca for stochastic canonical correlation analysis. Advances in neural information processing systems, 34:14056-14068, 2021.
[44] Eun Jeong Min, Eric C Chi, and Hua Zhou. Tensor canonical correlation analysis. Stat, 8(1):e253, 2019.
[45] Mark S Monmonier and Fay Evanko Finn. Improving the interpretation of geographical canonical correlation models. The Professional Geographer, 25(2):140-142, 1973.
[46] Masaki Nakanishi, Yijun Wang, Yu-Te Wang, and Tzyy-Ping Jung. A comparison study of canonical correlation analysis based methods for detecting steady-state visual evoked potentials. PloS one, 10(10):e0140703, 2015.
[47] Toru Ogura, Yasunori Fujikoshi, and Takakazu Sugiyama. A variable selection criterion for two sets of principal component scores in principal canonical correlation analysis. Communications in Statistics-Theory and Methods, 42(12):2118-2135, 2013.
[48] Aileme Omogbai. Application of multiview techniques to NHANES dataset. CoRR, abs/1608.04783, 2016.
[49] Luca Oneto and Silvia Chiappa. Fairness in machine learning. In *Recent Trends in Learning From Data*, pages 155–196. Springer, 2020.
[50] Jaakko Peltonen, Wen Xu, Timo Nummenmaa, and Jyrki Nummenmaa. Fair neighbor embedding. 2023.
[51] Harold Pimentel, Zhiyue Hu, and Haiyan Huang. Biclustering by sparse canonical correlation analysis. Quantitative Biology, 6(1):56-67, 2018.
[52] Miao Qi, Owen Cahan, Morgan A Foreman, Daniel M Gruen, Amar K Das, and Kristin P Bennett. Quantifying representativeness in randomized clinical trials using machine learning fairness metrics. JAMIA Open, 4(3):ooab077, 09 2021.
[53] Mathew J Reeves, Cheryl D Bushnell, George Howard, Julia Warner Gargano, Pamela W Duncan, Gwen Lynch, Arya Khatiwoda, and Lynda Lisabeth. Sex differences in stroke: epidemiology, clinical presentation, medical care, and outcomes. The Lancet Neurology, 7(10):915-926, 2008.
[54] Juho Rousu, David D Agranoff, Olugbemiro Sodeinde, John Shawe-Taylor, and Delmiro Fernandez-Reyes. Biomarker discovery by sparse canonical correlation analysis of complex clinical phenotypes of tuberculosis and malaria. PLoS Comput Biol, 9(4):e1003018, 2013.
[55] Samira Samadi, Uthaipon Tantipongpipat, Jamie H Morgenstern, Mohit Singh, and Santosh Vempala. The price of fair pca: One extra dimension. Advances in neural information processing systems, 31, 2018.
[56] Biplab K Sarkar and Chiranjib Chakraborty. Dna pattern recognition using canonical correlation algorithm. Journal of biosciences, 40(4):709-719, 2015.
[57] Steven V Schell and William A Gardner. Programmable canonical correlation analysis: A flexible framework for blind adaptive spatial filtering. IEEE Transactions on Signal Processing, 43(12):2898-2908, 1995.
[58] Jose A Seoane, Colin Campbell, Ian NM Day, Juan P Casas, and Tom R Gaunt. Canonical correlation analysis for gene-based pleiotropy discovery. PLoS Comput Biol, 10(10):e1003876, 2014.
[59] J. Sha, J. Bao, K. Liu, S. Yang, Z. Wen, J. Wen, Y. Cui, B. Tong, J. H. Moore, A. J. Saykin, C. Davatzikos, Q. Long, L. Shen, and Alzheimer's Disease Neuroimaging Initiative. Preference matrix guided sparse canonical correlation analysis for mining brain imaging genetic associations in alzheimer's disease. Methods, 218:27-38, 2023.
[60] Li Shen and Paul M. Thompson. Brain imaging genomics: Integrated analysis and machine learning. Proceedings of the IEEE, 108(1):125-162, 2020.
[61] Xiao-Bo Shen, Qi-Song Sun, and Yuan-Hai Yuan. Orthogonal canonical correlation analysis and its application in feature fusion. In Information Fusion (FUSION), 2013 16th International Conference on, pages 151–157. IEEE, 2013.
[62] Michael J Sullivan. Distribution of edaphic diatoms in a mississippi salt marsh: A canonical correlation analysis. Journal of Phycology, 18(1):130-133, 1982.