Dissertation/ Thesis

On the efficient determination of Hessian matrix sparsity pattern : algorithms and data structures

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: On the efficient determination of Hessian matrix sparsity pattern : algorithms and data structures
Συγγραφείς: Sultana, Marzia, University of Lethbridge. Faculty of Arts and Science
Συνεισφορές: Hossain, Shahadat
Στοιχεία εκδότη: University of Lethbridge, Dept. of Mathematics and Computer Science
Department of Mathematics and Computer Science
Arts and Science
Έτος έκδοσης: 2016
Συλλογή: University of Lethbridge Institutional Repository
Θεματικοί όροι: algorithmic differentiation tools, black-box gradient, direction vectors, graph coloring, greedy CPR algorithm, sparsity patterns
Περιγραφή: Evaluation of the Hessian matrix of a scalar function is a subproblem in many numerical optimization algorithms. For large-scale problems often the Hessian matrix is sparse and structured, and it is preferable to exploit such information when available. Using symmetry in the second derivative values of the components it is possible to detect the sparsity pattern of the Hessian via products of the Hessian matrix with specially chosen direction vectors. We use graph coloring methods and employ efficient sparse data structures to implement the sparsity pattern detection algorithms.
Τύπος εγγράφου: thesis
Περιγραφή αρχείου: application/pdf
Γλώσσα: English
Relation: Thesis (University of Lethbridge. Faculty of Arts and Science); https://hdl.handle.net/10133/4601
Διαθεσιμότητα: https://hdl.handle.net/10133/4601
Αριθμός Καταχώρησης: edsbas.6AE438DC
Βάση Δεδομένων: BASE
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