Successive Element Correction Algorithms for Sparse Unconstrained Optimization
This paper presents a successive element correction algorithm and a secant modification of this algorithm. The new algorithms are designed to use the gradient evaluations as efficiently as possible in forming the approximate Hessian. The estimate of the q-convergence and r-convergence rates show that the new algorithms may have good local convergence properties. Some restricted numerical results and comparisons with some previously established algorithms suggest the new algorithms have some promise to be efficient in practice.
Citable link to this pagehttps://hdl.handle.net/1911/101735
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- CAAM Technical Reports