On the Krylov subspace methods based on tensor format for positive definite Sylvester tensor equations. - Fatemeh Panjeh Ali Beik; Farid Saberi Movahed; Salman Ahmadi-Asl (Numer. Linear Algebra Appl., 2016)

On global Hessenberg based methods for solving Sylvester matrix equations. - Mohammed Heyouni; Farid Saberi Movahed; Azita Tajaddini (Comput. Math. Appl., 2019)

Feature selection based on regularization of sparsity based regression models by hesitant fuzzy correlation. - Mahla Mokhtia; Mahdi Eftekhari; Farid Saberi Movahed (Appl. Soft Comput., 2020)

A tensor format for the generalized Hessenberg method for solving Sylvester tensor equations. - Mohammed Heyouni; Farid Saberi Movahed; Azita Tajaddini (J. Comput. Appl. Math., 2020)

Supervised feature selection by constituting a basis for the original space of features and matrix factorization. - Farid Saberi Movahed; Mahdi Eftekhari; Mohammad Mohtashami (Int. J. Mach. Learn. Cybern., 2020)

Regularizing extreme learning machine by dual locally linear embedding manifold learning for training multi-label neural network classifiers. - Mohammad Rezaei-Ravari; Mahdi Eftekhari; Farid Saberi Movahed (Eng. Appl. Artif. Intell., 2021)

Two New Variants of the Simpler Block GMRES Method with Vector Deflation and Eigenvalue Deflation for Multiple Linear Systems. - Azita Tajaddini; Gang Wu; Farid Saberi Movahed; Najmeh Azizi Zadeh (J. Sci. Comput., 2021)

Dual-manifold regularized regression models for feature selection based on hesitant fuzzy correlation. - Mahla Mokhtia; Mahdi Eftekhari; Farid Saberi Movahed (Knowl. Based Syst., 2021)

On restarted and deflated block FOM and GMRES methods for sequences of shifted linear systems. - Lakhdar Elbouyahyaoui; Mohammed Heyouni; Azita Tajaddini; Farid Saberi Movahed (Numer. Algorithms, 2021)

High dimensionality reduction by matrix factorization for systems pharmacology. - Adel Mehrpooya; Farid Saberi Movahed; Najmeh Azizi Zadeh; Mohammad Rezaei-Ravari; Farshad Saberi-Movahed; Mahdi Eftekhari; Iman Tavassoly (Briefings Bioinform., 2022)

Decoding clinical biomarker space of COVID-19: Exploring matrix factorization-based feature selection methods. - Farshad Saberi-Movahed; Mahyar Mohammadifard; Adel Mehrpooya; Mohammad Rezaei-Ravari; Kamal Berahmand; Mehrdad Rostami; Saeed Karami; Mohammad Najafzadeh; Davood Hajinezhad; Mina Jamshidi; Farshid Abedi; Mahtab Mohammadifard; et al. (Comput. Biol. Medicine, 2022)

Dual Regularized Unsupervised Feature Selection Based on Matrix Factorization and Minimum Redundancy with application in gene selection. - Farid Saberi-Movahed; Mehrdad Rostami; Kamal Berahmand; Saeed Karami; Prayag Tiwari; Mourad Oussalah 002; Shahab S. Band (Knowl. Based Syst., 2022)

How Fuzzy Concepts Contribute to Machine Learning - Mahdi Eftekhari; Adel Mehrpooya; Farid Saberi-Movahed; Vicenç Torra (Springer, 2022)

Deep Metric Learning with Soft Orthogonal Proxies. - Farshad Saberi-Movahed; Mohammad Kazem Ebrahimpour; Farid Saberi-Movahed; Monireh Moshavash; Dorsa Rahmatian; Mahvash Mohazzebi; Mahdi Shariatzadeh; Mahdi Eftekhari (CoRR, 2023)

Unsupervised feature selection guided by orthogonal representation of feature space. - Mahsa Samareh Jahani; Gholamreza Aghamollaei; Mahdi Eftekhari; Farid Saberi-Movahed (Neurocomputing, 2023)

Graph Regularized Nonnegative Matrix Factorization for Community Detection in Attributed Networks. - Kamal Berahmand; Mehrnoush Mohammadi; Farid Saberi-Movahed; Yuefeng Li; Yue Xu 001 (IEEE Trans. Netw. Sci. Eng., 2023)

Unsupervised feature selection based on variance-covariance subspace distance. - Saeed Karami; Farid Saberi-Movahed; Prayag Tiwari; Pekka Marttinen; Sahar Vahdati (Neural Networks, 2023)

Nonnegative Matrix Factorization in Dimensionality Reduction: A Survey. - Farid Saberi-Movahed; Kamal Berahmand; Razieh Sheikhpour; Yuefeng Li; Shirui Pan (CoRR, 2024)

Low-Redundant Unsupervised Feature Selection based on Data Structure Learning and Feature Orthogonalization. - Mahsa Samareh Jahani; Farid Saberi-Movahed; Mahdi Eftekhari; Gholamreza Aghamollaei; Prayag Tiwari (Expert Syst. Appl., 2024)

Deep Nonnegative Matrix Factorization with Joint Global and Local Structure Preservation. - Farid Saberi-Movahed; Bitasta Biswas; Prayag Tiwari; Jens Lehmann 001; Sahar Vahdati (Expert Syst. Appl., 2024)

On applying deflation and flexible preconditioning to the adaptive Simpler GMRES method for Sylvester tensor equations. - Azita Tajaddini; Farid Saberi-Movahed; Xian-Ming Gu; Mohammed Heyouni (J. Frankl. Inst., 2024)

A Self-Representation Learning Method for Unsupervised Feature Selection using Feature Space Basis. - Prayag Tiwari; Farid Saberi Movahed; Saeed Karami; Farshad Saberi-Movahed; Jens Lehmann 001; Sahar Vahdati (Trans. Mach. Learn. Res., 2024)

Bilinear Self-Representation for Unsupervised Feature Selection with Structure Learning. - Hossein Nasser Assadi; Faranges Kyanfar; Farid Saberi-Movahed; Abbas Salemi (Neurocomputing, 2025)

A similarity measure based on subspace distance for spectral clustering. - Nadimeh Naseri; Mahdi Eftekhari; Farid Saberi-Movahed; Mehdi Radjabalipour; Lluis A. Belanche (Neurocomputing, 2025)

Robust semi-supervised multi-label feature selection based on shared subspace and manifold learning. - Razieh Sheikhpour; Mehrnoush Mohammadi; Kamal Berahmand; Farid Saberi-Movahed; Hassan Khosravi (Inf. Sci., 2025)

A Comprehensive Survey on Spectral Clustering with Graph Structure Learning. - Kamal Berahmand; Farid Saberi-Movahed; Razieh Sheikhpour; Yuefeng Li; Mahdi Jalili (CoRR, 2025)

Simultaneous outlier detection and elimination in hyperspectral unmixing via weighted non-negative matrix tri-factorization. - Yasin Hashemi-Nazari; Farid Saberi-Movahed; Azita Tajaddini; Catarina Moreira; Xin Ning 001; Prayag Tiwari (Mach. Learn., 2025)

Robust oblique projection and weighted NMF for hyperspectral unmixing. - Yasin Hashemi-Nazari; Azita Tajaddini; Farid Saberi-Movahed; Fernando Alonso-Fernandez; Prayag Tiwari (Pattern Recognit., 2026)