A modular system of algorithms for unconstrained minimization
ACM Transactions on Mathematical Software (TOMS)
Numerical recipes: the art of scientific computing
Numerical recipes: the art of scientific computing
How bad are the BFGS and DFP methods when the objective function is quadratic?
Mathematical Programming: Series A and B
Cancellation errors in quasi Newton methods
SIAM Journal on Scientific and Statistical Computing
Practical methods of optimization; (2nd ed.)
Practical methods of optimization; (2nd ed.)
Remark on “Algorithm 500: Minimization of Unconstrained Multivariate Functions [E4]”
ACM Transactions on Mathematical Software (TOMS)
Computational Optimization and Applications
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It has recently been shown that cancellation errors in a quasi-Newton method can increase without bound as the method converges. A simple test is presented to determine when cancellation errors could lead to significant contamination of the approximating matrix.