Results 11 to 20 of about 147,801 (260)
Decentralized Quasi-Newton Methods [PDF]
IEEE Transactions on Signal Processing, 2017 We introduce the decentralized Broyden-Fletcher-Goldfarb-Shanno (D-BFGS) method as a variation of the BFGS quasi-Newton method for solving decentralized optimization problems. The D-BFGS method is of interest in problems that are not well conditioned, making first order decentralized methods ineffective, and in which second order information is not ...
Eisen, Mark +2 more
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Quasi-Newton’s method for multiobjective optimization
Journal of Computational and Applied Mathematics, 2014 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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THE NEW RANK ONE CLASS FOR UNCONSTRAINED PROBLEMS SOLVING
Science Journal of University of Zakho, 2023 One of the most well-known methods for unconstrained problems is the quasi-Newton approach, iterative solutions. The great precision and quick convergence of the quasi-Newton methods are well recognized. In this work, the new algorithm for the symmetric
Ahmed Mustafa
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Self-Scaling Variable Metric in Constrained Optimization [PDF]
Al-Rafidain Journal of Computer Sciences and Mathematics, 2020 In this paper, we investigated of a new self-scaling by use quasi-Newton method and conjugate gradient method. The new algorithm satisfies a quasi-newton condition and mutually conjugate, and practically proved its efficiency when compared with the well ...
Eman Hamed, Marwa Hamad
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Correlation and realization of quasi-Newton methods of absolute optimization [PDF]
Компьютерные исследования и моделирование, 2016 Newton and quasi-Newton methods of absolute optimization based on Cholesky factorization with adaptive step and finite difference approximation of the first and the second derivatives.
Anastasiya Borisovna Sviridenko +1 more
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A New Theoretical Result for Quasi-Newton Formulae for Unconstrained Optimization [PDF]
Al-Rafidain Journal of Computer Sciences and Mathematics, 2005 The recent measure function of Byrd and Nocedal [3] is considered and simple proofs of some its properties are given. It is then shown that the AL-Bayati (1991) formulae satisfy a least change property with respect to this new measure .The new formula ...
Basim Hassan
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On the Convergence Rate of Quasi-Newton Methods on Strongly Convex Functions with Lipschitz Gradient
Mathematics, 2023 The main results of the study of the convergence rate of quasi-Newton minimization methods were obtained under the assumption that the method operates in the region of the extremum of the function, where there is a stable quadratic representation of the ...
Vladimir Krutikov +3 more
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Algorithms, 2021 Gradient-based methods are popularly used in training neural networks and can be broadly categorized into first and second order methods. Second order methods have shown to have better convergence compared to first order methods, especially in solving ...
S. Indrapriyadarsini +4 more
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Self-decisive algorithm for unconstrained optimization problems as in biomedical image analysis
Frontiers in Computational Neuroscience, 2022 This study describes the construction of a new algorithm where image processing along with the two-step quasi-Newton methods is used in biomedical image analysis.
Farah Jaffar +4 more
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Diagonal quasi-Newton updating formula using log-determinant norm [PDF]
, 2015 Quasi-Newton method has been widely used in solving unconstrained optimization problems. The popularity of this method is due to the fact that only the gradient of the objective function is required at each iterate. Since second derivatives (Hessian) are
Chen, Chuei Yee +3 more
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