Derivative-Free Global Optimization Algorithms: Bayesian Method and Lipschitzian Approaches

19 Apr 2019 Jiawei Zhang

In this paper, we will provide an introduction to the derivative-free optimization algorithms which can be potentially applied to train deep learning models. Existing deep learning model training is mostly based on the back propagation algorithm, which updates the model variables layers by layers with the gradient descent algorithm or its variants... (read more)

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