Results 11 to 20 of about 66,605 (263)
ZOOpt: a toolbox for derivative-free optimization
Science China Information Sciences, 2022 SCIENCE CHINA Information Sciences, 2022.
Yu-Ren Liu +4 more
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Inexact Derivative-Free Optimization for Bilevel Learning [PDF]
Journal of Mathematical Imaging and Vision, 2021 AbstractVariational regularization techniques are dominant in the field of mathematical imaging. A drawback of these techniques is that they are dependent on a number of parameters which have to be set by the user. A by-now common strategy to resolve this issue is to learn these parameters from data.
Matthias J. Ehrhardt, Lindon Roberts
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Derivative-free optimization methods [PDF]
Acta Numerica, 2019 In many optimization problems arising from scientific, engineering and artificial intelligence applications, objective and constraint functions are available only as the output of a black-box or simulation oracle that does not provide derivative information. Such settings necessitate the use of methods for derivative-free, or zeroth-order, optimization.
Jeffrey Larson 0001 +2 more
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A Derivative-Free Method for Structured Optimization Problems [PDF]
SIAM Journal on Optimization, 2021 Structured optimization problems are ubiquitous in fields like data science and engineering. The goal in structured optimization is using a prescribed set of points, called atoms, to build up a solution that minimizes or maximizes a given function. In the present paper, we want to minimize a black-box function over the convex hull of a given set of ...
Cristofari A., Rinaldi F.
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Mathematics, 2022 This article considers a box-constrained global optimization problem for Lipschitz continuous functions with an unknown Lipschitz constant. The well-known derivative-free global search algorithm DIRECT (DIvide RECTangle) is a promising approach for such ...
Linas Stripinis, Remigijus Paulavičius
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Derivative-free optimization for optical chirality enhancement [PDF]
EPJ Web of ConferencesWe adopt a multi-objective optimization approach to design one-dimensional photonic crystals with large optical chirality enhancements. We show that this technique allows for a large design flexibility in terms of selected materials and operational ...
Pellegrini Giovanni +5 more
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Journal of Inequalities and Applications, 2018 This paper focuses on a class of nonlinear optimization subject to linear inequality constraints with unavailable-derivative objective functions. We propose a derivative-free trust-region methods with interior backtracking technique for this optimization.
Jing Gao, Jian Cao
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A fire spread simulator to support tactical management decisions for Mediterranean landscapes
Frontiers in Forests and Global Change, 2023 The use of fire simulation tools has become a regular feature of support systems for fuel management decisions at landscape level. Considering the spatial nature of fire in the evaluation of risk and the definition of fire mitigation goals is an ongoing ...
Jose Ramon Gonzalez-Olabarria +12 more
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Life, 2021 Integrative modeling of macromolecular assemblies requires stochastic sampling, for example, via MCMC (Markov Chain Monte Carlo), since exhaustively enumerating all structural degrees of freedom is infeasible.
Satwik Pasani, Shruthi Viswanath
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Derivative-Free Optimal Iterative Methods
Computational Methods in Applied Mathematics, 2010 AbstractIn this study, we develop an optimal family of derivative-free iterative methods. Convergence analysis shows that the methods are fourth order convergent, which is also verified numerically. The methods require three functional evaluations during each iteration. Though the methods are independent of derivatives, computa-
Sanjay Kumar Khattri, Ravi P. Agarwal
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