Zobrazeno 1 - 10
of 1 156
pro vyhledávání: '"Saunders, Michael A"'
Autor:
Brust, Johannes J, Saunders, Michael A
For linear systems $Ax=b$ we develop iterative algorithms based on a sketch-and-project approach. By using judicious choices for the sketch, such as the history of residuals, we develop weighting strategies that enable short recursive formulas. The p
Externí odkaz:
http://arxiv.org/abs/2407.00746
Autor:
Świrydowicz, Kasia, Koukpaizan, Nicholson, Alam, Maksudul, Regev, Shaked, Saunders, Michael, Peleš, Slaven
Linear solvers are major computational bottlenecks in a wide range of decision support and optimization computations. The challenges become even more pronounced on heterogeneous hardware, where traditional sparse numerical linear algebra methods are
Externí odkaz:
http://arxiv.org/abs/2401.13926
We introduce an iterative solver named MINARES for symmetric linear systems $Ax \approx b$, where $A$ is possibly singular. MINARES is based on the symmetric Lanczos process, like MINRES and MINRES-QLP, but it minimizes $\|Ar_k\|$ in each Krylov subs
Externí odkaz:
http://arxiv.org/abs/2310.01757
Publikováno v:
SIAM Journal on Scientific Computing, 2023
We consider the generalized successive overrelaxation (GSOR) method for solving a class of block three-by-three saddle-point problems. Based on the necessary and sufficient conditions for all roots of a real cubic polynomial to have modulus less than
Externí odkaz:
http://arxiv.org/abs/2208.07499
Publikováno v:
SIAM Journl. Sci. Comput. 45(2), 2023
We propose iterative projection methods for solving square or rectangular consistent linear systems Ax = b. Existing projection methods use sketching matrices (possibly randomized) to generate a sequence of small projected subproblems, but even the s
Externí odkaz:
http://arxiv.org/abs/2207.07615
The conjugate gradient (CG) method is a classic Krylov subspace method for solving symmetric positive definite linear systems. We introduce an analogous semi-conjugate gradient (SCG) method for unsymmetric positive definite linear systems. Unlike CG,
Externí odkaz:
http://arxiv.org/abs/2206.02951
Autor:
Świrydowicz, Kasia, Koukpaizan, Nicholson, Alam, Maksudul, Regev, Shaked, Saunders, Michael, Peleš, Slaven
Publikováno v:
In Parallel Computing March 2025 123
Autor:
Gao, Wei, Lamb, Joseph J., Graham, David, Manda, Bhargavi, Dahlberg, Clinton J., Huff, E. Wesley, Saunders, Michael, Tripp, Matthew L.
Publikováno v:
In Journal of Functional Foods January 2025 124
In time series analysis, when fitting an autoregressive model, one must solve a Toeplitz ordinary least squares problem numerous times to find an appropriate model, which can severely affect computational times with large data sets. Two recent algori
Externí odkaz:
http://arxiv.org/abs/2112.12994
Autor:
Regev, Shaked, Chiang, Nai-Yuan, Darve, Eric, Petra, Cosmin G., Saunders, Michael A., Świrydowicz, Kasia, Peleš, Slaven
We propose a solution strategy for linear systems arising in interior method optimization, which is suitable for implementation on hardware accelerators such as graphical processing units (GPUs). The current gold standard for solving these systems is
Externí odkaz:
http://arxiv.org/abs/2110.03636