Order by:
[Title],
[Author],
[Editor],
[Year] 

A. K. M. Shahadat Hossain, Trond Steihaug
Computing a Sparse Jacobian Matrix by Rows and Columns
Article in
Optimization Methods and Software, 1998 
Theory & Techniques: graph coloring, Sparsity


Shahadat Hossain, Trond Steihaug
Computing Sparse Jacobian Matrices Optimally
Automatic Differentiation: Applications, Theory, and Implementations, Springer,
2005 
Theory & Techniques: Sparsity


Trond Steihaug, A. K. M. Shahadat Hossain
Graph Coloring and the Estimation of Sparse Jacobian Matrices with Segmented Columns
Department of Informatics, University of Bergen, 1997 
Theory & Techniques: graph coloring, Jacobianvector product, Sparsity


Shahadat Hossain, Trond Steihaug
Graph coloring in the estimation of sparse derivative matrices: Instances and applications
Article in
Discrete Appl. Math., Elsevier Science Publishers B. V.,
2008 
Theory & Techniques: graph coloring, Sparsity


A. K. M. Shahadat Hossain
On the Computation of Sparse Jacobian Matrices and Newton Steps
Ph.D. thesis,
Department of Informatics, University of Bergen, 1998 
Theory & Techniques: Sparsity


Shahadat Hossain, Trond Steihaug
Optimal Direct Determination of Sparse Jacobian Matrices
Department of Informatics, University of Bergen, Norway, 2003 
Theory & Techniques: Sparsity


Shahadat Hossain, Nasrin Hakim Mithila
Pattern graph for sparse Hessian matrix determination
Article in
Special issue of Optimization Methods & Software: Advances in Algorithmic Differentiation, Taylor & Francis,
2018 
not yet classified


Shahadat Hossain, Trond Steihaug
Reducing the Number of AD Passes for Computing a Sparse Jacobian Matrix
Automatic Differentiation of Algorithms: From Simulation to Optimization, Springer,
2002 
Theory & Techniques: Sparsity


Shahadat Hossain, Trond Steihaug
Sparsity Issues in the Computation of Jacobian Matrices
Conference proceeding,
Proceedings of the International Symposium on Symbolic and Algebraic Computing (ISSAC), ACM,
2002 
Theory & Techniques: Jacobianvector product, Sparsity
