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Convergence Analysis of Metaheuristics
2009In this tutorial, an overview on the basic techniques for proving convergence of metaheuristics to optimal (or sufficiently good) solutions is given. The presentation is kept as independent of special metaheuristic fields as possible by the introduction of a generic metaheuristic algorithm.
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On the Convergence Analysis of the MINLIP Estimator
IFAC Proceedings Volumes, 2012Abstract This paper discusses convergence properties of the recently introduced MINimal LIPschitz (MINLIP) estimator for the identification of a monotone Wiener model from noiseless input-output measurements. This estimator is entirely build around the notion of complexity control, making the approach conceptual quite different from traditional ...
Pelckmans, K., Dai, L., Bai, E.
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Convergence analysis of the Hopmoc method
International Journal of Computer Mathematics, 2009The Hopmoc method combines concepts of the modified method of characteristics (MMOC) and the Hopscotch method. First, Hopmoc resembles Hopscotch because it decomposes the set of grid points into two subsets. Namely, both subsets have their unknowns separately updated within one semi-step. Furthermore, each subset undergoes one explicit and one implicit
Oliveira, Simoni R. de +2 more
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Supercalm Multifunctions For Convergence Analysis
Set-Valued Analysis, 2006zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Convergence analysis of the ChebFilterCG algorithm
Numerical Linear Algebra with Applications, 2017SummaryThe ChebFilterCG algorithm, proposed by Golub, Ruiz, and Touhami [SIAM J. Matrix Anal. Appl. 29 (2007), pp. 774‐795] is an iterative method that combines Chebyshev filter and conjugate gradient for solving symmetric positive definite linear systems with multiple right‐hand sides.
Miloud Sadkane, Ahmed Touhami
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2004
Proving convergence of the various optimization algorithms is a delicate exercise. In general, it is helpful to consider local and global convergence patterns separately. The local convergence rate of an algorithm provides a useful benchmark for comparing it to other algorithms. On this basis, Newton’s method wins hands down. However, the tradeoffs are
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Proving convergence of the various optimization algorithms is a delicate exercise. In general, it is helpful to consider local and global convergence patterns separately. The local convergence rate of an algorithm provides a useful benchmark for comparing it to other algorithms. On this basis, Newton’s method wins hands down. However, the tradeoffs are
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Analysis of the Convergence and Generalization of AA1
Journal of Parallel and Distributed Computing, 1995AA1 is an incremental learning algorithm for Adaptive Self-Organizing Concurrent Systems (ASOCS). ASOCS are self-organizing, dynamically growing networks of computing nodes. AA1 learns by discrimination and implements knowledge in a distributed fashion over all the nodes. This paper reviews AA1 from the perspective of convergence and generalization.
Giraud-Carrier, Christophe +1 more
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A convergence analysis of the ADM and an application
Applied Mathematics and Computation, 2005The Adomian decomposition method (ADM) is applied to the modified Korteweg-de Vries equation. This method yields exact and approximate solutions of nonlinear problems without transforming the equation. The solution is expressed in a series and the basis functions are obtained via recursions.
Dogan Kaya, Ibrahim E. Inan
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Convergence Analysis of Affinity Propagation
2009Recently, Frey & Dueck proposed a novel clustering algorithm named affinity propagation (AP), which has been shown to be powerful as it costs much less time and reaches much lower error. However, its convergence property has not been studied in theory. In this paper, we focus on convergence property of the algorithm.
Jian Yu 0001, Caiyan Jia
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Convergence Structures in Numerical Analysis
Zeitschrift für Analysis und ihre Anwendungen, 1996The paper deals — under the viewpoint of topology — with discrete Cauchy spaces, which are spaces where a discrete Cauchy structure (t,\mathcal C) (with t being a ...
Gähler, Siegfried +1 more
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