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- W2068150956 abstract "A new approach for computing a sparsity pattern for a Hessian is presented: nonlinearity information is propagated through the function evaluation yielding the nonzero structure. A complexity analysis of the proposed algorithm is given. Once the sparsity pattern is available, coloring algorithms can be applied to compute a seed matrix. To evaluate the product of the Hessian and the seed matrix, a vector version for evaluating second order adjoints is analysed. New drivers of ADOL-C are provided implementing the presented algorithms. Runtime analyses are given for some problems of the CUTE collection." @default.
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- W2068150956 title "Computing sparse Hessians with automatic differentiation" @default.
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- W2068150956 doi "https://doi.org/10.1145/1322436.1322439" @default.
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