A Preconditioned Unconstrained Optimization Method for Training Multilayer Feed-forward Neural Network

Öz

Non-linear unconstrained optimization  methods constitute excellent neural network training methods characterized by their simplicity and efficiency. In this paper, we propose a new preconditioned conjugate gradient neural network training algorithm which guarantees descent property with standard Wolfe condition. Encouraging numerical experiments verify that the proposed algorithm provides fast and stable convergence.

Anahtar Kelimeler

• Unconstrained optimization,Neural network,Descent property

Kaynakça

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