Results 31 to 40 of about 14,949,583 (325)
Journal of Computational and Applied Mathematics, 2019 The progressive iterative approximation (PIA) is an iterative method for solving the linear system of equations corresponding to the interpolation problem.
A. Ebrahimi, G. B. Loghmani
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Convergence Rates for Projective Splitting [PDF]
SIAM Journal on Optimization, 2019 This version adds references to the extragradient ...
Johnstone, Patrick R. +1 more
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Convergence Rate Analysis [PDF]
, 2009 After showing the convergence of the two numerical methods for Frobenius-Perron operators in the previous chapter, we further investigate the convergence rate problem for them. Keller’s stochastic stability result for a class of Markov operators will be studied first, which leads to his first proof of the L1-norm convergence rate O(ln n/n) for Ulam’s ...
Jiu Ding, Aihui Zhou
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Open Mathematics, 2023 This article presents an approximation of discrete Markov decision processes with small noise on Borel spaces with an infinite horizon and an expected total discounted cost by the corresponding deterministic Markov process.
Portillo-Ramírez Gustavo +3 more
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Convergence Rate and Locality of Improved Overlap Fermions [PDF]
, 2002 We construct new Ginsparg-Wilson fermions for QCD by inserting an approximately chiral Dirac operator - which involves ingredients of a perfect action - into the overlap formula.
Albanese +71 more
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Journal of Computational and Applied Mathematics, 2018 Recently, Mao (2015) developed a new explicit method, called the truncated Euler–Maruyama (EM) method, for the nonlinear SDE and established the strong convergence theory under the local Lipschitz condition plus the Khasminskii-type condition.
Liangjian Hu, Xiaoyue Li, X. Mao
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Rate of Convergence for Cardy’s Formula [PDF]
Communications in Mathematical Physics, 2014 We show that crossing probabilities in 2D critical site percolation on the triangular lattice in a piecewise analytic Jordan domain converge with power law rate in the mesh size to their limit given by the Cardy-Smirnov formula. We use this result to obtain new upper and lower bounds of exp(O(sqrt(log log R))) R^(-1/3) for the probability that the ...
Nachmias, Asaf +2 more
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A Novel Stochastic Stratified Average Gradient Method: Convergence Rate and Its Complexity [PDF]
IEEE International Joint Conference on Neural Network, 2017 SGD (Stochastic Gradient Descent) is a popular algorithm for large scale optimization problems due to its low iterative cost. However, SGD can not achieve linear convergence rate as FGD (Full Gradient Descent) because of the inherent gradient variance ...
Aixiang Chen +4 more
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On convergence rate of the randomized Kaczmarz method
Linear Algebra and its Applications, 2018 For consistent system of linear equations with the coefficient matrix being flat, we conduct an exact closed-form formula for the mean squared error of the iterate generated by the randomized Kaczmarz method, which completes the existing closed-form ...
Z. Bai, Wen-Ting Wu
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On the Nonergodic Convergence Rate of an Inexact Augmented Lagrangian Framework for Composite Convex Programming [PDF]
Mathematics of Operations Research, 2016 In this paper, we consider the linearly constrained composite convex optimization problem, whose objective is a sum of a smooth function and a possibly nonsmooth function. We propose an inexact augmented Lagrangian (IAL) framework for solving the problem.
Ya-Feng Liu, Xin Liu, Shiqian Ma
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