Publication: Collected Matrix Derivative Results for Forward and Reverse Mode Algorithmic Differentiation
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Collected Matrix Derivative Results for Forward and Reverse Mode Algorithmic Differentiation

- incollection -
 

Author(s)
Mike B. Giles

Published in
Advances in Automatic Differentiation

Editor(s)
Christian H. Bischof, H. Martin Bücker, Paul D. Hovland, Uwe Naumann, J. Utke

Year
2008

Publisher
Springer

Abstract
This paper collects together a number of matrix derivative results which are very useful in forward and reverse mode algorithmic differentiation. It highlights in particular the remarkable contribution of a 1948 paper by Dwyer and Macphail which derives the linear and adjoint sensitivities of a matrix product, inverse and determinant, and a number of related results motivated by applications in multivariate analysis in statistics.

Cross-References
Bischof2008AiA

AD Theory and Techniques
Hierarchical Approach

BibTeX
@INCOLLECTION{
         Giles2008CMD,
       title = "Collected Matrix Derivative Results for Forward and Reverse Mode Algorithmic
         Differentiation",
       doi = "10.1007/978-3-540-68942-3_4",
       author = "Mike B. Giles",
       abstract = "This paper collects together a number of matrix derivative results which are very
         useful in forward and reverse mode algorithmic differentiation. It highlights in particular the
         remarkable contribution of a 1948 paper by Dwyer and Macphail which derives the linear and adjoint
         sensitivities of a matrix product, inverse and determinant, and a number of related results
         motivated by applications in multivariate analysis in statistics.",
       crossref = "Bischof2008AiA",
       pages = "35--44",
       booktitle = "Advances in Automatic Differentiation",
       publisher = "Springer",
       editor = "Christian H. Bischof and H. Martin B{\"u}cker and Paul D. Hovland and Uwe
         Naumann and J. Utke",
       isbn = "978-3-540-68935-5",
       issn = "1439-7358",
       year = "2008",
       ad_theotech = "Hierarchical Approach"
}


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