New Quasi-Newton Method
On Application of a New Quasi-Newton Algorithm for Solving Optimal Control Problems
... a New Quasi-Newton method by adopting the quasi-Newton method algorithm to obtain the solution of the following scalar, linear, optimal control problem of the form: ...
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Quasi-Newton Method: A New Direction
... that quasi-Newton methods can be interpreted as Gaussian regressors using algebraic structure to weaken prior knowledge, in exchange for lower computational ...Bayesian quasi-Newton ...
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Prediction of Flow Duration Curves for Ungauged Basins with Quasi Newton Method
... quite new approach, called the EREFDC model, for estimating the parameters of the FDC for which the parameters of the FDC are obtained with quasi-Newton ...The method is applied to 72 ...
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Coupling of Partitioned Physics Codes with Quasi-Newton Methods
... TABLE VI: 2D flexible beam. Number of iterations to reach convergence, averaged over the number of time steps, for the flexible tail benchmark problem for the various QN methods. The Jacobian at the end of the iterations ...
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Extra multistep BFGS updates in quasi Newton methods
... the new method EA1 shows significant improvements, when compared with the standard, single-step, BFGS method and ...the method from which it was developed (namely, A1), it is not so superior ...
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Stochastic quasi-Newton molecular simulations
... The idea of reducing or even eliminating critical slowing down by scaling is also present in the Fourier acceleration method for lattice field theory 关14兴. The application of Fou- rier acceleration has been ...
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Matrix Transformations and Quasi Newton Methods
... section method to construct a natural sequence of finite sequences converging to a ...a new method of approximation which is a direct consequence of the quasi-Newton method, ...
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7. A Modification of Quasi-Newton (DFP) Method for Solving Unconstrained Optimization Problems
... the new algorithm (New5) with the standard algorithm (DFP), The numerical results of the new algorithm is better than the standard algorithm, As we notice that (NOI), (NOF) of the standard algorithm are ...
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A quasi-Newton optimal method for the global linearisation of the output feedback pole assignment
... powerful method referred to as global linearisation which has addressed both solvability conditions and computation of ...The method is based on the asymptotic linearisation of the pole assignment map ...
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A stochastic quasi Newton method for molecular simulations
... (BFGS) method using only gradient information in subsequent sampling ...the method unaffected but substantially reduce the storage and compu- tational requirements are of great importance for the value of ...
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A nonmonotone adaptive trust region algorithm for symmetric nonlinear equations
... for quasi-Newton method with a suitable line ...inexact quasi-Newton algorithm [26] and the trust region algorithms [27-30] were ...BFGS method is proposed by Li and Fukushima ...
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A Quasi-Newton Approach to Nonsmooth Convex Optimization Problems in Machine Learning
... hinge loss. The main idea of their optimized cutting plane algorithm, OCAS, is to perform a line search along the line connecting two successive iterates of a bundle method solver. Recently they have extended OCAS ...
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Efficient solvers for time-dependent problems: a review of IMEX, LATIN, PARAEXP and PARAREAL algorithms for heat-type problems with potential use of approximate exponential integrators and reduced-order models
... For time-dependent problems, one can adopt a greedy incremental strategy during time by adapting/enriching the low-dimensional subspace when the principal components are changing during time. But the price to pay is to ...
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PROTECT SENSITIVE KNOWLEDGE IN DATA MINING CLUSTERING ALGORITHM
... Earlier research regarding DDoS detection using ANN method, does not address the parameters in ANN that underlie the accuracy level in detecting DDoS attacks. Therefore in this study we do research focuses on ANN ...
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Neural Network Training By Gradient Descent Algorithms: Application on the Solar Cell
... ABSTRACT: This present paper deals with the parameter determination of solar cell by using an artificial neural network trained at every time, separately, by one algorithm among the optimization algorithms of gradient ...
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Two-level nonlinear elimination based preconditioners for inexact Newton methods with application in shocked duct flow calculation
... [5] X.-C. C AI , D. E. K EYES , AND L. M ARCINKOWSK I , Nonlinear additive Schwarz preconditioners and appli- cations in computational fluid dynamics, Internat. J. Numer. Methods Fluids, 40 (2002), pp. 1463–1470. [6] ...
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Global Convergence of Online Limited Memory BFGS
... Global convergence of an online (stochastic) limited memory version of the Broyden-Fletcher- Goldfarb-Shanno (BFGS) quasi-Newton method for solving optimization problems with stochastic objectives ...
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Quasi-Newton Methods for the Acceleration of Multi-Physics Codes
... performing method, with a clear benefit in retaining the old Jacobian at the start of each time ...good method in Figure 9 at different time steps for both re-use and resetting of the ...
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Quasi Monte Carlo Estimation in Generalized Linear Mixed Model with Correlated Random Effects
... We generate K = 50, 000 integration nodes on the unit cube C 20 = [ 0,1 ) 20 using the square root sequences. We then use those integration nodes to approximate the integrated log-likelihood as the one given in (11), and ...
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A Novel Iteration Class for Solution of Nonlinear Equation
... In this paper, recent iteration formula is offered to solve the roots of the nonlinear equations. Tables and results show that this method has better performance than other methods. It can be seen from the ...
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