6 papers · 1 filter
Multidimensional extrapolated global proximal gradient and applications for image processing
Abdeslem Hafid Bentbib, Khalide Jbilou, Ridwane Tahiri
The proximal gradient method is a generic technique introduced to tackle the non-smoothness in optimization problems, wherein the objective function is expressed as the sum of a di…
Extended block Hessenberg process for the evaluation of matrix functions
A. H. Bentbib, M. EL Ghomari, K. Jbilou +1
In the present paper, we propose a block variant of the extended Hessenberg process for computing approximations of matrix functions and other problems producing large-scale matric…
Einstien-Multidimensional Extrapolation methods
A. H. Bentbib, K. Jbilou, R. Tahiri
In this paper, we present a new framework for the recent multidimensional extrapolation methods: Tensor Global Minimal Polynomial (TG-MPE) and Tensor Global Reduced Rank Extrapolat…
Tensor Golub Kahan based on Einstein product
Anas El Hachimi, Khalide Jbilou, Mustapha Hached +1
The Singular Value Decomposition (SVD) of matrices is a widely used tool in scientific computing. In many applications of machine learning, data analysis, signal and image processi…
A Rational Krylov Subspace Method for the Computation of the Matrix Exponential Operator
H. Barkouki, A. H. Bentbib, K. Jbilou
The computation of approximating e^tA B, where A is a large sparse matrix and B is a rectangular matrix, serves as a crucial element in numerous scientific and engineering calculat…
A tensor bidiagonalization method for higher-order singular value decomposition with applications
Anas El Hachimi, Khalide Jbilou, Ahmed Ratnani +1
The need to know a few singular triplets associated with the largest singular values of third-order tensors arises in data compression and extraction. This paper describes a new me…