Training Artificial Neural Networks by Generalized Likelihood Ratio Method: Exploring Brain-like Learning to Improve Robustness

1 code implementation • 31 Jan 2019 • Li Xiao, Yijie Peng, Jeff Hong, Zewu Ke, Shuhuai Yang

In this work, we propose a generalized likelihood ratio method capable of training the artificial neural networks with some biological brain-like mechanisms,. e. g., (a) learning by the loss value, (b) learning via neurons with discontinuous activation and loss functions.

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