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Matrix Computations with Applications

Research group The group Numerical Linear Algebra studies algorithms for complex numerical problems, usually involving computations on very large matrices.

The results of this research are important for applications in engineering and natural science that require computation-intensive numerical problems to be solved. Along with the theoretical work and the exploration of applications in, e.g., systems and control theory, the group also contributes to the further development of standard software libraries, such as LAPACK, ScaLAPACK, and the SLICOT library within the NICONET project.

Research leader

Bo Kågström
Professor emeritus, professor
E-mail
Email

Overview

Participating departments and units at Umeå University

Department of Computing Science

Research area

Computing science

Research projects

StratiGraph and MCS Toolbox
Research area: Computing science
Duration 1 January 1998
Type of project Research project

Latest publications

Foundations of Computational Mathematics, Springer 2020, Vol. 20, (3) : 423-450
Dmytryshyn, Andrii; Johansson, Stefan; Kågström, Bo; et al.
NLAFET Consortium; Umeå University 2019
Kågström, Bo; Myllykoski, Mirko; Karlsson, Lars; et al.
NLAFET Consortium; Umeå University 2019
Myllykoski, Mirko; Kjelgaard Mikkelsen, Carl Christian; Schwarz, Angelika Beatrix; et al.
NLAFET Consortium; Umeå University 2018
Myllykoski, Mirko; Karlsson, Lars; Kågström, Bo; et al.
Parallel Processing and Applied Mathematics. PPAM 2017: Part 1, Springer 2018 : 579-589
Eljammaly, Mahmoud; Karlsson, Lars; Kågström, Bo
SIAM Journal on Scientific Computing, Society for Industrial and Applied Mathematics 2018, Vol. 40, (2) : C157-C180
Adlerborn, Björn; Karlsson, Lars; Kågström, Bo
ICPE '18 Companion of the 2018 ACM/SPEC International Conference on Performance Engineering, ACM Digital Library 2018 : 5-8
Eljammaly, Mahmoud; Karlsson, Lars; Kågström, Bo
Report / UMINF, 17.19
Eljammaly, Mahmoud; Karlsson, Lars; Kågström, Bo
Report / UMINF, 17.10
Adlerborn, Björn; Kjelgaard Mikkelsen, Carl Christian; Karlsson, Lars; et al.
Report / UMINF, 17.11
Myllykoski, Mirko; Kjelgaard Mikkelsen, Carl Christian; Karlsson, Lars; et al.

News - Computing Science

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New thesis shows how AI can be used to categorise news articles and improve contextual advertising.

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Hannah's research on biased AI
Published: 2024-04-14

Hanna Devinney defends their thesis on biased AI on 18 April 2024.

Latest update: 2021-09-06