Distributionally robust nonnegative matrix factorization with self-paced adaptive multi-loss fusion

Barkhoda, Wafa; Seyedi, Seyed Amjad; Gillis, Nicolas; Akhlaghian Tab, Fardin

doi:10.1016/j.ins.2025.122823

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Distributionally robust nonnegative matrix factorization with self-paced adaptive multi-loss fusion

Barkhoda, Wafa; Seyedi, Seyed Amjad; Gillis, Nicolas et al.

2026 • In Information Sciences, 728, p. 122823

Peer Reviewed verified by ORBi

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https://hdl.handle.net/20.500.12907/53534

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10.1016/j.ins.2025.122823

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Disciplines :

Computer science

Author, co-author :

Barkhoda, Wafa

Seyedi, Seyed Amjad ; Université de Mons - UMONS > Recherche > Service ERC Unit - Matrix Theory and Optimization

Gillis, Nicolas ; Université de Mons - UMONS > Faculté Polytechnique > Service de Mathématique et Recherche opérationnelle

Akhlaghian Tab, Fardin

Language :

English

Title :

Distributionally robust nonnegative matrix factorization with self-paced adaptive multi-loss fusion

Publication date :

February 2026

Journal title :

Information Sciences

ISSN :

0020-0255

eISSN :

1872-6291

Publisher :

Elsevier BV

Volume :

728

Pages :

122823

Peer reviewed :

Peer Reviewed verified by ORBi

Additional URL :

https://api.elsevier.com/content/article/PII:S0020025525009594?httpAccept=text/xml

Research unit :

F151 - Mathématique et Recherche opérationnelle

Research institute :

R300 - Institut de Recherche en Technologies de l'Information et Sciences de l'Informatique
R450 - Institut NUMEDIART pour les Technologies des Arts Numériques

European Projects :

HE - 101085607 - eLinoR - Beyond Low-Rank Factorizations

Funders :

HORIZON EUROPE European Research Council
European Union

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since 03 November 2025

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Gillis, N., Nonnegative Matrix Factorization, 2020, Society for Industrial and Applied Mathematics, Philadelphia, PA.
Li, Z., Tang, J., He, X., Robust structured nonnegative matrix factorization for image representation. IEEE Trans. Neural Netw. Learn. Syst. 29:5 (2018), 1947–1960.
Luo, W., Wu, Z., Zhou, N., Hypergraph-based convex semi-supervised unconstraint symmetric matrix factorization for image clustering. Inf. Sci., 680, 2024, 121138.
Yu, S., Mao, B., Zhou, Y., Liu, Y., Yi, C., Li, F., Yao, D., Xu, P., San Liang, X., Zhang, T., Large-scale cortical network analysis and classification of MI-BCI tasks based on Bayesian nonnegative matrix factorization. IEEE Trans. Neural Syst. Rehabil. Eng. 32 (2024), 2187–2197.
Zhong, B., Wu, J.-S., Huang, W., Zheng, W.-S., Cluster structure augmented deep nonnegative matrix factorization with low-rank tensor learning. Inf. Sci., 670, 2024, 120585.
He, Z., Lin, Y., Lin, Z., Wang, C., Multi-label feature selection via similarity constraints with non-negative matrix factorization. Knowl.-Based Syst., 297, 2024, 111948.
Wang, B., Fan, J., Robust matrix completion with heavy-tailed noise. J. Am. Stat. Assoc. 120:550 (2025), 922–934.
Peng, J., Sun, W., Jiang, F., Chen, H., Zhou, Y., Du, Q., A general loss-based nonnegative matrix factorization for hyperspectral unmixing. IEEE Geosci. Remote Sens. Lett. 19 (2022), 1–5.
Lam, E.Y., Non-negative matrix factorization for images with Laplacian noise. 2008 IEEE Asia Pacific Conference on Circuits and Systems, 2008, 798–801.
Kong, D., Ding, C., Huang, H., Robust nonnegative matrix factorization using L21-norm. International Conference on Information and Knowledge Management, 2011, 673–682.
Du, L., Li, X., Shen, Y.-D., Robust nonnegative matrix factorization via half-quadratic minimization. 2012 IEEE 12th International Conference on Data Mining, 2012, 201–210.
Peng, S., Ser, W., Lin, Z., Chen, B., Robust sparse nonnegative matrix factorization based on maximum correntropy criterion. 2018 IEEE International Symposium on Circuits and Systems (ISCAS), 2018, 1–5.
Liutkus, A., Fitzgerald, D., Badeau, R., Cauchy nonnegative matrix factorization. 2015 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, 2015, 1–5.
Bertsimas, D., Gupta, V., Kallus, N., Data-driven robust optimization. Math. Program. 167 (2018), 235–292.
Gao, H., Nie, F., Cai, W., Huang, H., Robust capped norm nonnegative matrix factorization: capped norm NMF. Proceedings of the 24th ACM International on Conference on Information and Knowledge Management, 2015, 871–880.
Guan, N., Liu, T., Zhang, Y., Tao, D., Davis, L.S., Truncated Cauchy non-negative matrix factorization. IEEE Trans. Pattern Anal. Mach. Intell. 41:1 (2019), 246–259.
Scarf, H., A min-max solution of an inventory problem. Studies in the Mathematical Theory of Inventory and Production, 1958, Stanford University Press, Redwood City, CA, 201–209.
Cheng, J., Li-Yang Chen, R., Najm, H.N., Pinar, A., Safta, C., Watson, J.-P., Distributionally robust optimization with principal component analysis. SIAM J. Optim. 28:2 (2018), 1817–1841.
Zhu, S., Xie, L., Zhang, M., Gao, R., Xie, Y., Distributionally robust weighted k-nearest neighbors. Advances in Neural Information Processing Systems, vol. 35, 2022, 29088–29100.
Faccini, D., Maggioni, F., Potra, F.A., Robust and distributionally robust optimization models for linear support vector machine. Comput. Oper. Res., 147, 2022, 105930.
Gillis, N., Hien, L.T.K., Leplat, V., Tan, V.Y.F., Distributionally robust and multi-objective nonnegative matrix factorization. IEEE Trans. Pattern Anal. Mach. Intell. 44:8 (2022), 4052–4064.
Barkhoda, W., Seyedi, A., Gillis, N., Akhlaghian Tab, F., Instance-wise distributionally robust nonnegative matrix factorization. Pattern Recognit., 169, 2026, 111732.
Soleymanbaigi, S., Seyedi, A., Akhlaghian Tab, F., Daneshfar, F., Encoder-decoder nonnegative matrix factorization with β-divergence for data clustering. Pattern Recognit., 171, 2026, 112211.
Xiong, H., Kong, D., Nie, F., Cauchy balanced nonnegative matrix factorization. Artif. Intell. Rev. 56:10 (2023), 11867–11903.
Cavazos, J.S., Fessler, J.A., Balzano, L., ALPCAH: sample-wise heteroscedastic PCA with tail singular value regularization. 2023 International Conference on Sampling Theory and Applications (SAMPTA), 2023, 1–6.
Yu, Z., Dong, G., Liu, H., Sar image quality assessment: from sample-wise to class-wise. Remote Sens., 15(8), 2023.
Eiras, F., Alfarra, M., Torr, P., Kumar, M.P., Dokania, P.K., Ghanem, B., Bibi, A., Ancer: anisotropic certification via sample-wise volume maximization. Trans. Mach. Learn. Res., 2022.
Chen, L., Wu, C.-T., Lin, C.-H., Dai, R., Liu, C., Clarke, R., Yu, G., Van Eyk, J.E., Herrington, D.M., Wang, Y., Swcam: estimation of subtype-specific expressions in individual samples with unsupervised sample-wise deconvolution. Bioinformatics 38:5 (2021), 1403–1410.
Wang, H., Yang, W., Guan, N., Cauchy sparse NMF with manifold regularization: a robust method for hyperspectral unmixing. Knowl.-Based Syst., 184, 2019, 104898.
Kumar, M., Packer, B., Koller, D., Self-paced learning for latent variable models. Advances in Neural Information Processing Systems, vol. 23, 2010, 1189–1197.
Liu, Z., Feng, X., Wang, Y., Zuo, W., Self-paced learning enhanced neural matrix factorization for noise-aware recommendation. Knowl.-Based Syst., 213, 2021, 106660.
Huang, Z., Ren, Y., Pu, X., Pan, L., Yao, D., Yu, G., Dual self-paced multi-view clustering. Neural Networks 140 (2021), 184–192.
Seyedi, S.A., Ghodsi, S.S., Akhlaghian, F., Jalili, M., Moradi, P., Self-paced multi-label learning with diversity. Asian Conference on Machine Learning, vol. 101, 2019, PMLR, 790–805.
Zhao, Q., Meng, D., Jiang, L., Xie, Q., Xu, Z., Hauptmann, A., Self-paced learning for matrix factorization. Proc. AAAI Conf. Artif. Intell., 29(1), Feb. 2015.
Zhu, X., Zhang, Z., Improved self-paced learning framework for nonnegative matrix factorization. Pattern Recognit. Lett. 97 (2017), 1–7.
Huang, S., Zhao, P., Ren, Y., Li, T., Xu, Z., Self-paced and soft-weighted nonnegative matrix factorization for data representation. Knowl.-Based Syst. 164 (2019), 29–37.
Candès, E.J., Li, X., Ma, Y., Wright, J., Robust principal component analysis?. J. ACM, 58(3), 2011.
Zhang, L., Chen, Z., Zheng, M., He, X., Robust non-negative matrix factorization. Front. Electr. Electron. Eng. China 6:2 (2011), 192–200.
Daubechies, I., DeVore, R., Fornasier, M., Güntürk, C.S., Iteratively reweighted least squares minimization for sparse recovery. Commun. Pure Appl. Math. 63:1 (2010), 1–38.
Wang, Q., He, X., Jiang, X., Li, X., Robust bi-stochastic graph regularized matrix factorization for data clustering. IEEE Trans. Pattern Anal. Mach. Intell. 44:1 (2022), 390–403.
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., et al. Scikit-learn: machine learning in Python. J. Mach. Learn. Res. 12 (2011), 2825–2830.
Yang, J., Shi, R., Wei, D., Liu, Z., Zhao, L., Ke, B., Pfister, H., Ni, B., MedMNIST v2 - a large-scale lightweight benchmark for 2D and 3D biomedical image classification. Sci. Data, 10(1), 2023, 41.
Lee, D., Seung, H.S., Algorithms for non-negative matrix factorization. Advances in Neural Information Processing Systems, vol. 13, 2000, MIT Press, 535–541.
Wei, J., Tong, C., Wu, B., He, Q., Qi, S., Yao, Y., Teng, Y., An entropy weighted nonnegative matrix factorization algorithm for feature representation. IEEE Trans. Neural Netw. Learn. Syst. 34:9 (2023), 5381–5391.
Xiong, H., Kong, D., Elastic nonnegative matrix factorization. Pattern Recognit. 90 (2019), 464–475.
Salahian, N., Tab, F.A., Seyedi, S.A., Chavoshinejad, J., Deep autoencoder-like NMF with contrastive regularization and feature relationship preservation. Expert Syst. Appl., 214, 2023, 119051.
Zhao, R., Tan, V.Y.F., Online nonnegative matrix factorization with outliers. IEEE Trans. Signal Process. 65:3 (2017), 555–570.