Optimal accumulation of Jacobian matrices by elimination methods on the dual computational graph
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[1] M. Powell,et al. On the Estimation of Sparse Jacobian Matrices , 1974 .
[2] A. Griewank,et al. On the calculation of Jacobian matrices by the Markowitz rule , 1991 .
[3] John R. Gilbert,et al. A Note on the NP-Completeness of Vertex Elimination on Directed Graphs , 1980, SIAM J. Algebraic Discret. Methods.
[4] N. Metropolis,et al. Equation of State Calculations by Fast Computing Machines , 1953, Resonance.
[5] Charles L. Lawson,et al. Basic Linear Algebra Subprograms for Fortran Usage , 1979, TOMS.
[6] Andreas Griewank,et al. Evaluating derivatives - principles and techniques of algorithmic differentiation, Second Edition , 2000, Frontiers in applied mathematics.
[7] Ellis Horowitz,et al. Fundamentals of Computer Algorithms , 1978 .
[8] Alfred V. Aho,et al. Compilers: Principles, Techniques, and Tools , 1986, Addison-Wesley series in computer science / World student series edition.
[9] Uwe Naumann,et al. Markowitz-Type Heuristics for Computing Jacobian Matrices Efficiently , 2003, International Conference on Computational Science.
[10] Uwe Naumann,et al. Cheaper Jacobians by Simulated Annealing , 2002, SIAM J. Optim..
[11] Webb Miller,et al. Software for Roundoff Analysis of Matrix Algorithms , 1980 .
[12] Romesh M. Jessani,et al. Comparison of Single- and Dual-Pass Multiply-Add Fused Floating-Point Units , 1998, IEEE Trans. Computers.
[13] Andreas Griewank,et al. Accumulating Jacobians as chained sparse matrix products , 2003, Math. Program..
[14] Martin Berz,et al. Computational differentiation : techniques, applications, and tools , 1996 .
[15] Uwe Naumann,et al. Prospects for Simulated Annealing Algorithms in Automatic Differentiation , 2001, SAGA.
[16] John D. Pryce,et al. Performance Issues for Vertex Elimination Methods in Computing Jacobians Using Automatic Differentiation , 2002, International Conference on Computational Science.
[17] Andreas Griewank,et al. Automatic Differentiation of Algorithms: From Simulation to Optimization , 2000, Springer New York.
[18] U. Naumann. Elimination techniques for cheap Jacobians , 2000 .
[19] C. Bischof,et al. Efficient computation of gradients and Jacobians by dynamic exploitation of sparsity in automatic differentiation , 1996 .
[20] Mohammad R. Haghighat,et al. Hierarchical approaches to automatic differentiation , 1996 .
[21] Giorgio Gambosi,et al. Complexity and Approximation , 1999, Springer Berlin Heidelberg.
[22] Giorgio Gambosi,et al. Complexity and approximation: combinatorial optimization problems and their approximability properties , 1999 .
[23] D. Rose,et al. Algorithmic aspects of vertex elimination on directed graphs. , 1975 .
[24] R. E. Wengert,et al. A simple automatic derivative evaluation program , 1964, Commun. ACM.
[25] L. Perelman,et al. Hydrostatic, quasi‐hydrostatic, and nonhydrostatic ocean modeling , 1997 .
[26] S. Forth,et al. AD tools and prospects for optimal AD in CFD flux Jacobian calculations , 2000 .
[27] David S. Johnson,et al. Computers and Intractability: A Guide to the Theory of NP-Completeness , 1978 .
[28] Uwe Naumann,et al. Efficient calculation of Jacobian matrices by optimized application of the chain rule to computational graphs , 1999 .