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The paper surveys some recently proposed algorithms for unconstrained minimization when second derivative of the objective function is sparse. Updating and estimation procedures are considered from the efficiency point of view. Special attention is given to the case where the Hessian has a band structure. A new strategy for the choice of the step is also discussed and some numerical results on a specially designed test function are presented.
|Title of host publication||Sparse Matrices and Their Uses|
|Editors||I. S Duff|
|Place of Publication||London|
|Number of pages||32|
|Publication status||Published - 1981|