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Showing 1 to 3 of 3 for “"second-order optimisation"”.
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Advances in Meta-Learning, Robustness, and Second-Order Optimisation in Deep Learning
… can improve learning by solving the underlying optimisation problem more efficiently. Machine learning methods are typically very data hungry. Although modern machine learning has been hugely effective in solving real-world problems, these success stories are largely limited to settings where …
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An improvement of back propagation algorithm using halley third order optimisation method for classification problems
… efficient method. This algorithm utilises first order optimisation method namely Gradient Descent (GD) method which attempts to minimise the error of network. Nevertheless, some major issues need to be considered. The GD method not performed well in large scale applications and when higher …
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Advances in Optimisation of Model Parameters and Hyperparameters for Neural Networks
… to minimise some loss metric, so the chosen optimisation algorithm plays a fundamental role in the training process — both through the optimisation logic itself, and the auxiliary *hyperparameters* which configure the optimiser’s behaviour. Moreover, Machine Learning tasks often demand unique …