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• W2143672845 abstract "Conjugate gradient methods constitute excellent neural network training methods which are characterized by their simplicity and their very low memory requirements. In this paper, we propose a new spectral conjugate gradient method which guarantees sufficient descent using any line search, avoiding thereby the usually inefficient restarts. Moreover, we establish the global convergence of our proposed method under some assumptions. Experimental results provide evidence that our proposed method is preferable and in general superior to the classical conjugate gradient methods in terms of efficiency and robustness." @default.
• W2143672845 created "2016-06-24" @default.
• W2143672845 creator A5024258131 @default.
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• W2143672845 date "2012-02-01" @default.
• W2143672845 modified "2023-09-28" @default.
• W2143672845 title "AN IMPROVED SPECTRAL CONJUGATE GRADIENT NEURAL NETWORK TRAINING ALGORITHM" @default.
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• W2143672845 doi "https://doi.org/10.1142/s0218213011004757" @default.
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