Multi-point Directional Minimization for Conjugate Gradient Algorithm

Jarosław Bilski

doi:10.1007/978-3-032-03705-3_2

2026-01-01

PRE

Jarosław Bilski *

Jacek Smoląg

DOI：10.1007/978-3-032-03705-3_2

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共轭梯度（CG）算法是训练神经网络的一种广泛应用的方法。其计算量最大的步骤是方向最小化。本文介绍了一种CG算法的新型改进方法，该方法加速了方向最小化，从而显著减少了计算时间。提出的改进方法在选定的测试案例中进行评估，并将其性能与经典的CG方法进行了比较。

Keyword:

feedforward neural network

supervised learning

conjugate gradient algorithm

parallel computation

期刊

ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING, ICAISC 2025, PT I

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technical university czestochowa

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1.3K

论文数: 1.5K

被引数: 1

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