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The convergence rates of iterative methods for solving a linear system $\mathbf{A} x = b$ typically depend on the condition number of the matrix $\mathbf{A}$.
On best conditioned matrices
G. E. Forsythe and E. G. Straus · 1955
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Condition numbers and equilibration of matrices
A. van der Sluis · 1969
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Optimal preconditioners of a given sparsity pattern
A. Greenbaum and G. H. Rodrigue · 1989
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Econometric analysis
William H. Greene · 1990
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Is a simple diagonal scaling the best preconditioner for conjugate gradients on supercomputers?
Giorgio Pini and Giuseppe Gambolati · 1990
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Large cliques elude the metropolis process
Mark Jerrum · 1992
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Coloring random and semi-random k-colorable graphs
Avrim Blum and Joel Spencer · 1995
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Parallel preconditioning with sparse approximate inverses
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Iterative Methods for Solving Linear Systems
Anne Greenbaum · 1997
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A comparative study of sparse approximate inverse preconditioners
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Heuristics for semirandom graph problems
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The multiplicative weights update method: a meta-algorithm and applications
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