Abstract: Selecting an appropriate step size is critical in Gradient Descent algorithms used to train Neural Networks for Deep Learning tasks. A small value of the step size leads to slow convergence, ...
Gradient variance errors in gradient-based search methods are largely mitigated using momentum, however the bias gradient errors may fail the numerical search methods in reaching the true optimum. We ...
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