An optimized second order stochastic learning algorithm for neural network training
This paper proposes an improved stochastic second order learning algorithm for supervised neural network training. The proposed algorithm, named bounded stochastic diagonal Levenberg-Marquardt (B-SDLM), utilizes both gradient and curvature information to achieve fast convergence while requiring only...
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| Format: | Article |
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Elsevier B.V.
2016
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