Zobrazeno 1 - 10
of 479
pro vyhledávání: '"Saad, Yousef"'
This paper describes the software package Cucheb, a GPU implementation of the filtered Lanczos procedure for the solution of large sparse symmetric eigenvalue problems. The filtered Lanczos procedure uses a carefully chosen polynomial spectral transf
Externí odkaz:
http://arxiv.org/abs/2409.15053
Autor:
Seghouane, Abd-Krim, Saad, Yousef
Given a set of $p$ symmetric (real) matrices, the Orthogonal Joint Diagonalization (OJD) problem consists of finding an orthonormal basis in which the representation of each of these $p$ matrices is as close as possible to a diagonal matrix. We argue
Externí odkaz:
http://arxiv.org/abs/2409.02005
In this paper, we consider the iterative solution of linear algebraic equations under the condition that matrix-vector products with the coefficient matrix are computed only partially. At the same time, non-computed entries are set to zeros. We assum
Externí odkaz:
http://arxiv.org/abs/2407.01098
Anderson Acceleration (AA) is a popular algorithm designed to enhance the convergence of fixed-point iterations. In this paper, we introduce a variant of AA based on a Truncated Gram-Schmidt process (AATGS) which has a few advantages over the classic
Externí odkaz:
http://arxiv.org/abs/2403.14961
This paper explores variants of the subspace iteration algorithm for computing approximate invariant subspaces. The standard subspace iteration approach is revisited and new variants that exploit gradient-type techniques combined with a Grassmann man
Externí odkaz:
http://arxiv.org/abs/2306.10379
Publikováno v:
SIAM Journal on Matrix Analysis and Applications, Volume 45, Issue 1, pp. 1-827 (2024)
This paper develops a new class of nonlinear acceleration algorithms based on extending conjugate residual-type procedures from linear to nonlinear equations. The main algorithm has strong similarities with Anderson acceleration as well as with inexa
Externí odkaz:
http://arxiv.org/abs/2306.00325
Autor:
Beik, Fatemeh P. A., Saad, Yousef
This paper introduces the notion of tubular eigenvalues of third-order tensors with respect to T-products of tensors and analyzes their properties. A focus of the paper is to discuss relations between tubular eigenvalues and two alternative definitio
Externí odkaz:
http://arxiv.org/abs/2305.06323
Nonlinear acceleration methods are powerful techniques to speed up fixed-point iterations. However, many acceleration methods require storing a large number of previous iterates and this can become impractical if computational resources are limited.
Externí odkaz:
http://arxiv.org/abs/2210.12573
This paper discusses parGeMSLR, a C++/MPI software library for the solution of sparse systems of linear algebraic equations via preconditioned Krylov subspace methods in distributed-memory computing environments. The preconditioner implemented in par
Externí odkaz:
http://arxiv.org/abs/2205.03224
Many modern machine learning algorithms such as generative adversarial networks (GANs) and adversarial training can be formulated as minimax optimization. Gradient descent ascent (GDA) is the most commonly used algorithm due to its simplicity. Howeve
Externí odkaz:
http://arxiv.org/abs/2110.02457