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Optimization Methods & Software, 2011
We propose a quasi-Newton line-search method that uses negative curvature directions for solving unconstrained optimization problems. In this method, the symmetric rank-one (SR1) rule is used to update the Hessian approximation. The SR1 update rule is known to have a good numerical performance; however, it does not guarantee positive definiteness of the updated matrix. We first discuss the details of the proposed algorithm and then concentrate on its practical behaviour. Our extensive computational study shows the potential of the proposed method from different angles, such as its performance compared with some other existing packages, the profile of its computations, and its large-scale adaptation. We then conclude the paper with the convergence analysis of the proposed method.
The Astronomical Journal, 2010
The Astronomical …, 2011
2009
The Carnegie Supernova Project is a five year survey being carried out at the Las Campanas Observatory to obtain high-quality light curves of 100 low-redshift Type Ia supernovae in a well-defined photometric system. In this paper, we present the first release of photometric data that contains the optical (ugriBV) light curves of 35 Type Ia supernovae, and near-infrared (YJHKs) light
2009
We propose a quasi-Newton method that uses negative curvature directions for solving unconstrained optimization problems. In this method, the symmetric rank-one (SR1) rule is used to update the Hessian approximation. The SR1 update rule is known to have a good numerical performance; however, it does not guarantee positive definiteness of the updated matrix. We first discuss the details of the proposed algorithm and then concentrate on its numerical efficiency.
Voluntas Revista Internacional de Filosofia, 2024
O presente texto é a tradução para o português brasileiro do artigo “Algorithmic Catastrophe — The Revenge of Contingency”
Research in Mathematics Education, 2019
Connecting curriculum development and research benefits both. Those designing curricula should ensure that their work is scientifically based and evaluated. Those studying existing curricula should understand the ways in which they were developed and validated (or not) and that a comprehensive evaluation program involves more than final outcomes. We use a curriculum research framework to draw implications for research in both development and evaluation projects. For each phase of the framework, we discuss how publishable research and curriculum development (R&D) might occur, as well as what opportunities there may be for evaluation research alone. In all cases, we briefly suggest methods.
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