2022
DOI: 10.1609/aaai.v36i11.21623
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A Stochastic Momentum Accelerated Quasi-Newton Method for Neural Networks (Student Abstract)

Abstract: Incorporating curvature information in stochastic methods has been a challenging task. This paper proposes a momentum accelerated BFGS quasi-Newton method in both its full and limited memory forms, for solving stochastic large scale non-convex optimization problems in neural networks (NN).

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