[9] Christopher M Bishop and Nasser M Nasrabadi. Pattern recognition and machine learning, volume 4. Springer, 2006.
[10] Dankmar Böhning. Multinomial logistic regression algorithm. Annals of the institute of Statistical Mathematics, 44(1):197-200, 1992.
[11] Emmanuel Candes and Benjamin Recht. Exact matrix completion via convex optimization. Communications of the ACM, 55(6):111-119, 2012.
[12] Moody T Chu, Robert E Funderlic, and Robert J Plemmons. Structured low rank approximation. Linear algebra and its applications, 366:157-172, 2003.
[13] Michael Elad and Michal Aharon. Image denoising via sparse and redundant representations over learned dictionaries. IEEE Transactions on Image processing, 15(12):3736-3745, 2006.
[14] Bruno César Feltes, Eduardo Bassani Chandelier, Bruno Iochins Grisci, and Márcio Dorn. Cumida: An extensively curated microarray database for benchmarking and testing of machine learning approaches in cancer research. Journal of Computational Biology, 26(4):376-386, 2019. PMID: 30789283.
[15] Mehrdad J Gangeh, Ahmed K Farahat, Ali Ghodsi, and Mohamed S Kamel. Supervised dictionary learning and sparse representation-a review. arXiv preprint arXiv:1502.05928, 2015.
[16] Mehrdad J Gangeh, Pouria Fewzee, Ali Ghodsi, Mohamed S Kamel, and Fakhri Karray. Multiview supervised dictionary learning in speech emotion recognition. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 22(6):1056-1068, 2014.
[17] Gene H Golub and Christian Reinsch. Singular value decomposition and least squares solutions. In Linear algebra, pages 134-151. Springer, 1971.
[18] Luigi Grippo and Marco Sciandrone. On the convergence of the block nonlinear gauss-seidel method under convex constraints. Operations research letters, 26(3):127-136, 2000.
[19] Roger A Horn and Charles R Johnson. Matrix analysis. Cambridge university press, 2012.
[20] Prateek Jain, Raghu Meka, and Inderjit Dhillon. Guaranteed rank minimization via singular value projection. Advances in Neural Information Processing Systems, 23, 2010.
[21] Prateek Jain, Praneeth Netrapalli, and Sujay Sanghavi. Low-rank matrix completion using alternating minimization. In Proceedings of the forty-fifth annual ACM symposium on Theory of computing, pages 665-674, 2013.
[22] Donghyun Kim, Chanyoung Park, Jinoh Oh, Sungyoung Lee, and Hwanjo Yu. Convolutional matrix factorization for document context-aware recommendation. In Proceedings of the 10th ACM conference on recommender systems, pages 233-240, 2016.
[23] Guillaume Lecué and Shahar Mendelson. Sparse recovery under weak moment assumptions. Journal of the European Mathematical Society, 19(3):881-904, 2017.
[24] Yann LeCun and Corinna Cortes. MNIST handwritten digit database. 2010.
[25] Daniel D Lee and H Sebastian Seung. Learning the parts of objects by non-negative matrix factorization. Nature, 401(6755):788, 1999.
[26] Johannes Leuschner, Maximilian Schmidt, Pascal Fernsel, Delf Lachmund, Tobias Boskamp, and Peter Maass. Supervised non-negative matrix factorization methods for maldi imaging applications. Bioinformatics, 35(11):1940-1947, 2019.
[27] Zhengming Li, Zheng Zhang, Jie Qin, Zhao Zhang, and Ling Shao. Discriminative fisher embedding dictionary learning algorithm for object recognition. IEEE transactions on neural networks and learning systems, 31(3):786-800, 2019.
[28] Julien Mairal. Optimization with first-order surrogate functions. In International Conference on Machine Learning, pages 783-791, 2013.