6 citations · 9 across the 7 of their papers we have counts for
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A Robust Algebraic Domain Decomposition Preconditioner for Sparse Normal Equations
Hussam Al Daas, Pierre Jolivet, Jennifer Scott
Solving the normal equations corresponding to large sparse linear least-squares problems is an important and challenging problem. For very large problems, an iterative solver is ne…
Solving large linear least squares problems with linear equality constraints
Jennifer Scott, Miroslav Tuma
We consider the problem of efficiently solving large-scale linear least squares problems that have one or more linear constraints that must be satisfied exactly. Whilst some classi…
On time-parallel preconditioning for the state formulation of incremental weak constraint 4D-Var
Ieva Daužickaitė, Amos S. Lawless, Jennifer A. Scott +1
Using a high degree of parallelism is essential to perform data assimilation efficiently. The state formulation of the incremental weak constraint four-dimensional variational data…
Two-level Nyström--Schur preconditioner for sparse symmetric positive definite matrices
Hussam Al Daas, Tyrone Rees, Jennifer Scott
Randomized methods are becoming increasingly popular in numerical linear algebra. However, few attempts have been made to use them in developing preconditioners. Our interest lies…
Randomised preconditioning for the forcing formulation of weak constraint 4D-Var
Ieva Daužickaitė, Amos S. Lawless, Jennifer A. Scott +1
There is growing awareness that errors in the model equations cannot be ignored in data assimilation methods such as four-dimensional variational assimilation (4D-Var). If allowed…