BibTeX
@ARTICLE{
         Walther2008CSH,
       title = "Computing Sparse {H}essians with Automatic Differentiation",
       author = "Andrea Walther",
       publisher = "ACM",
       year = "2008",
       journal = "{ACM} Transaction on Mathematical Software",
       volume = "34",
       number = "1",
       pages = "3:1--3:15",
       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. Run-time analyses are
         given for some problems of the CUTE collection.",
       ad_area = "Optimization",
       ad_tools = "ADOL-C",
       ad_theotech = "Sparsity",
       url = "http://doi.acm.org/10.1145/1322436.1322439"
}