Results 51 to 60 of about 13,863,967 (339)
Mathematics, 2020 In this paper, Landweber iteration with a relaxation factor is proposed to solve nonlinear ill-posed integral equations. A compression multiscale Galerkin method that retains the properties of the Landweber iteration is used to discretize the Landweber ...
Rong Zhang, Fanchun Li, Xingjun Luo
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On the convergence rates of pairs of adjacent sequences
Journal of Numerical Analysis and Approximation Theory, 2020 In this paper we give a suitable definition for the pairs of adjacent (convergent) sequences of real numbers, we present some two-sided estimations which caracterize the order of convergence to its limits of some of these sequences and we give certain ...
Dorel I. Duca, Andrei Vernescu
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Strong convergence rates of semidiscrete splitting approximations for the stochastic Allen–Cahn equation [PDF]
IMA Journal of Numerical Analysis, 2018 This article analyses an explicit temporal splitting numerical scheme for the stochastic Allen–Cahn equation driven by additive noise in a bounded spatial domain with smooth boundary in dimension $d\leqslant 3$.
Charles-Edouard Br'ehier +2 more
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Smooth Function Approximation by Deep Neural Networks with General Activation Functions
Entropy, 2019 There has been a growing interest in expressivity of deep neural networks. However, most of the existing work about this topic focuses only on the specific activation function such as ReLU or sigmoid.
Ilsang Ohn, Yongdai Kim
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Convergence Rates for Generalized Descents [PDF]
The Electronic Journal of Combinatorics, 2011 d-descents are permutation statistics that generalize the notions of descents and inversions. It is known that the distribution of d-descents of permutations of length n satisfies a central limit theorem as n goes to infinity. We provide an explicit formula for the mean and variance of these statistics and obtain bounds on the rate of convergence using
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Optimal Convergence Rates for Nesterov Acceleration [PDF]
SIAM Journal on Optimization, 2018 In this paper, we study the behavior of solutions of the ODE associated to Nesterov acceleration. It is well-known since the pioneering work of Nesterov that the rate of convergence O(t 2) is optimal for the class of convex functions.
Jean-François Aujol +2 more
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On the Rate of Convergence of Greedy Algorithms
Mathematics, 2023 In this paper, a new criterion for the evaluation of the theoretical efficiency of a greedy algorithm is suggested. Using this criterion, we prove some results on the rate of convergence of greedy algorithms, which provide expansions. We consider both the case of Hilbert spaces and the more general case of Banach spaces. The new component of this paper
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Exact Worst-Case Convergence Rates of the Proximal Gradient Method for Composite Convex Minimization [PDF]
Journal of Optimization Theory and Applications, 2017 We study the worst-case convergence rates of the proximal gradient method for minimizing the sum of a smooth strongly convex function and a non-smooth convex function, whose proximal operator is available.
Adrien B. Taylor +2 more
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GROWTH RATES, QUALITY OF ECONOMIC GROWTH AND CONVERGENCE OF GROWTH RATES [PDF]
Annals of the University of Petrosani: Economics, 2021 The aim of this analysis is to examine methodological possibilities for defining the interdependence of the key categories of production theory. The ultimate goal of this paper is to define relationships pointing to the interdependence of growth rates ...
NADA TRIVIĆ, BOJANA TODIĆ
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Weak convergence rates of splitting schemes for the stochastic Allen–Cahn equation [PDF]
BIT Numerical Mathematics, 2018 This article is devoted to the analysis of the weak rates of convergence of schemes introduced by the authors in a recent work, for the temporal discretization of the one-dimensional stochastic Allen–Cahn equation driven by space-time white noise.
Charles-Edouard Br'ehier +1 more
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