Results 31 to 40 of about 36,010,976 (311)
The Gradient Discretisation Method [PDF]
, 2018 This monograph is dedicated to the presentation of the gradient discretisation method (GDM) and to some of its applications. It is intended for masters students, researchers and experts in the field of the numerical analysis of partial differential equations.The GDM is a framework which contains classical and recent discretisation schemes for diffusion
Droniou, Jérôme +4 more
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Geometrical Inverse Preconditioning for Symmetric Positive Definite Matrices
Mathematics, 2016 We focus on inverse preconditioners based on minimizing F ( X ) = 1 − cos ( X A , I ) , where X A is the preconditioned matrix and A is symmetric and positive definite. We present and analyze gradient-type methods to minimize F ( X )
Jean-Paul Chehab, Marcos Raydan
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Mathematical Model for Establishing the Time-Dependent Behavior of Rocks by the Gradient Method
Applied Sciences, 2022 In the underground activity domain, most problems related to mining pressure and mining stability need to be solved by taking into account the time behavior of rocks through an approach of the interaction amidst the rock massif, support system, time ...
Mihaela Toderas
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Differentially Quantized Gradient Methods
IEEE Transactions on Information Theory, 2022 Consider the following distributed optimization scenario. A worker has access to training data that it uses to compute the gradients while a server decides when to stop iterative computation based on its target accuracy or delay constraints. The server receives all its information about the problem instance from the worker via a rate-limited noiseless ...
Chung-Yi Lin +2 more
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One method for minimization a convex Lipschitz-continuous function of two variables on a fixed square [PDF]
Компьютерные исследования и моделирование, 2019 In the article we have obtained some estimates of the rate of convergence for the recently proposed by Yu. E.Nesterov method of minimization of a convex Lipschitz-continuous function of two variables on a square with a fixed side.
Dmitry Arkad'evich Pasechnyuk +1 more
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Mathematics, 2023 This paper considers a model for the accumulation of mutations in a population of mice with a weakened function of polymerases responsible for correcting DNA copying errors during cell division.
Raul Argun +4 more
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A Three-Term Conjugate Gradient Method with Sufficient Descent Property for Unconstrained Optimization [PDF]
, 2011 Conjugate gradient methods are widely used for solving large-scale unconstrained optimization problems, because they do not need the storage of matrices.
Hager W. W. +4 more
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Proximal-Proximal-Gradient Method [PDF]
Journal of Computational Mathematics, 2017 In this paper, we present the proximal-proximal-gradient method (PPG), a novel optimization method that is simple to implement and simple to parallelize.
Ernest K. Ryu, W. Yin
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Comparison the readings of gravity field and it‘s gradient potential
Қарағанды университетінің хабаршысы. Математика сериясы, 2019 The problem of studying the deep structure of the earth’s crust is one of the strategic directions of geophysical research, ensuring the development of Earth sciences.
М.О. Kenzhebayeva
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Accelerating Incremental Gradient Optimization with Curvature Information
, 2020 This paper studies an acceleration technique for incremental aggregated gradient ({\sf IAG}) method through the use of \emph{curvature} information for solving strongly convex finite sum optimization problems.
Nedich, Angelia +4 more
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