conjugate gradient descent search
PRP Type Direct Search Methods for Unconstrained Optimization
... direct search methods for solving ...some descent conjugate gradient methods to make use of the gradient ...These descent conjugate gradient methods for solving ...
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Modified nonlinear conjugate gradient method with sufficient descent condition for unconstrained optimization
... In this paper, an efficient modified nonlinear conjugate gradient method for solving unconstrained optimization problems is proposed. An attractive property of the modified method is that the generated ...
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Logistic regression with conjugate gradient descent for document classification
... use gradient descent as their optimization ...that conjugate gradient descent outperforms gradient descent because the method first computes the gradient to locate ...
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Global convergence of a modified conjugate gradient method
... efficient conjugate gradient method in practical ...line search is ...a descent modified PRP conjugate gradient method and proved its global ...line search has also been ...
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A Conjugate Gradient Method for Unconstrained Optimization Problems
... FR conjugate gradient method and the WYL conjugate gradient method is proposed for unconstrained optimization ...sufficient descent property under the strong Wolfe-Powell SWP line ...
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A DESCENT PRP CONJUGATE GRADIENT METHOD FOR UNCONSTRAINED OPTIMIZATION
... In summary, the convergence of the PRP method for general nonlinear function is uncertain, Powell’s example shows that when the function is not strongly convex, the PRP method may not converge even with an exact line ...
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Three New Hybrid Conjugate Gradient Methods for Optimization
... nonlinear conjugate gradient methods are presented, which produce sufficient descent search direction at every ...line search or the convexity of the objective function ...
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The effect of adaptive gain and adaptive momentum in improving training time of Gradient Descent back propagation algorithm on classification problems
... how conjugate gradient algorithm could be used to train multilayer feed forward neural ...a search is performed along conjugate directions, which generally leads to faster convergence than ...
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A New Descent Nonlinear Conjugate Gradient Method for Unconstrained Optimization
... Generally, the PRP method was much better than the FR method judging from the numerical calculation. When the objective function was convex, Polak and Ri- bie`re proved that the PRP method with the exact line ...
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A Modified FR Conjugate Gradient Method with Strong Wolfe Line Search
... FR conjugate gradient method has been disclosed, whose algorithm satisfies the descent property and the global convergence of this method can be guaranteed under some mild ...
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A new accelerated conjugate gradient method for large scale unconstrained optimization
... the search direction depends neither on the line search, nor on the convexity of objective ...accelerated conjugate gradient method (NACG) for large-scale unconstrained ...erated search ...
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Dai Kou type conjugate gradient methods with a line search only using gradient
... of conjugate gradient methods for the un- constrained nonlinear problems, the corresponding search direction is close to the direc- tion of the scaled memoryless BFGS ...ficient descent ...
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Three modified Polak Ribière Polyak conjugate gradient methods with sufficient descent property
... line search condition (). Grippo and Lucidi [] proposed new line search conditions, which can ensure that the PRP method is globally convergent for nonconvex ...line search in the numerical ...
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The Effect of Adaptive Gain and Adaptive Momentum in Improving Training Time of Gradient Descent Back Propagation Algorithm on Classification Problems
... how conjugate gradient algorithm could be used to train multilayer feed forward neural ...a search is performed along conjugate directions, which generally leads to faster convergence than ...
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1. First and second order training algorithms for artificial neural networks to detect the cardiac state
... steepest descent algorithm is based on first order Taylor’s series expansion, whereas the conjugate gradient algorithm is based on the second order Taylor’s ...steepest descent algorithm with ...
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Detection of Mobile Keyloggers Using Deep Learning
... the gradient of the ...Stochastic gradient descent faster depending on the problem than Batch gradient ...batch gradient descent ...
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A New Nonlinear Conjugate Gradient Method Based on the Scaled Matrix
... In this paper, a new type nonlinear conjugate gradient method based on the Scale Matrix is derived. The new method has the decent and globally convergent properties under some assumptions. Numerical results ...
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The Effect of Pre-Processing Techniques and Optimal Parameters selection on Back Propagation Neural Networks
... algorithms; gradient descent and gradient descent with momentum, both using the sigmoidal and hyperbolic tangent activation functions, coupled with pre-processing techniques are executed and ...
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Predictive Data Mining with Normalized Adaptive Training Method for Neural Networks
... error gradient graphs that second order methods were able to reach the set target of error gradient the order of 10 -5 ...error gradient value of ...error gradient even in 1000 ...final ...
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An Efficient Algorithm to Analyse the Cost Sensitive Measures on Datasets
... ABSTRACT: An efficient algorithm to analyse the cost sensitive measure is proposed. The main goal of this paper is to measure the sum of weighted sensitivity and specificity, total misclassification cost. To achieve the ...
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