Farid Saberi Movahed
Orcid: 0000-0003-2718-229X
According to our database1,
Farid Saberi Movahed authored at least 35 papers
between 2016 and 2026.
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Bibliography
2026
ACM Comput. Surv., April, 2026
Semi-supervised feature selection with concept factorization and robust label learning.
Pattern Recognit., 2026
Pattern Recognit., 2026
A Dual Autoencoder-like NMF with higher-order graph regularization for topic modeling.
Knowl. Based Syst., 2026
Unsupervised feature selection via graph-based proximity and structured autoencoder-like NMF.
Inf. Process. Manag., 2026
Joint sample-feature subspace learning via bidirectional reconstruction for feature selection.
Neurocomputing, 2026
Deep oblique projective autoencoder-like non-negative matrix factorization for robust image clustering.
Expert Syst. Appl., 2026
2025
Simultaneous outlier detection and elimination in hyperspectral unmixing via weighted non-negative matrix tri-factorization.
Mach. Learn., July, 2025
CoRR, January, 2025
Robust semi-supervised multi-label feature selection based on shared subspace and manifold learning.
Inf. Sci., 2025
Neurocomputing, 2025
Bilinear Self-Representation for Unsupervised Feature Selection with Structure Learning.
Neurocomputing, 2025
Proceedings of the IEEE International Conference on Data Mining, 2025
2024
A Self-Representation Learning Method for Unsupervised Feature Selection using Feature Space Basis.
Trans. Mach. Learn. Res., 2024
On applying deflation and flexible preconditioning to the adaptive Simpler GMRES method for Sylvester tensor equations.
J. Frankl. Inst., 2024
Deep Nonnegative Matrix Factorization with Joint Global and Local Structure Preservation.
Expert Syst. Appl., 2024
Low-Redundant Unsupervised Feature Selection based on Data Structure Learning and Feature Orthogonalization.
Expert Syst. Appl., 2024
2023
Neural Networks, September, 2023
Graph Regularized Nonnegative Matrix Factorization for Community Detection in Attributed Networks.
IEEE Trans. Netw. Sci. Eng., 2023
Neurocomputing, 2023
2022
Studies in Fuzziness and Soft Computing 416, Springer, ISBN: 978-3-030-94065-2, 2022
Dual Regularized Unsupervised Feature Selection Based on Matrix Factorization and Minimum Redundancy with application in gene selection.
Knowl. Based Syst., 2022
Decoding clinical biomarker space of COVID-19: Exploring matrix factorization-based feature selection methods.
Comput. Biol. Medicine, 2022
Briefings Bioinform., 2022
2021
On restarted and deflated block FOM and GMRES methods for sequences of shifted linear systems.
Numer. Algorithms, 2021
Dual-manifold regularized regression models for feature selection based on hesitant fuzzy correlation.
Knowl. Based Syst., 2021
Two New Variants of the Simpler Block GMRES Method with Vector Deflation and Eigenvalue Deflation for Multiple Linear Systems.
J. Sci. Comput., 2021
Regularizing extreme learning machine by dual locally linear embedding manifold learning for training multi-label neural network classifiers.
Eng. Appl. Artif. Intell., 2021
2020
Supervised feature selection by constituting a basis for the original space of features and matrix factorization.
Int. J. Mach. Learn. Cybern., 2020
A tensor format for the generalized Hessenberg method for solving Sylvester tensor equations.
J. Comput. Appl. Math., 2020
Feature selection based on regularization of sparsity based regression models by hesitant fuzzy correlation.
Appl. Soft Comput., 2020
2019
Comput. Math. Appl., 2019
2016
On the Krylov subspace methods based on tensor format for positive definite Sylvester tensor equations.
Numer. Linear Algebra Appl., 2016