Titlebook: Analysis of Images, Social Networks and Texts; 8th International Co Wil M. P. van der Aalst,Vladimir Batagelj,Elena Tu Conference proceedin

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Wil M. P. van der Aalst,Vladimir Batagelj,Elena Tu

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ONYM

,Digitale Produktion: Bottom-up-?konomie, Adam on simple reinforcement learning tasks and tend to be more stable and less strict to hyperparameters selection. Considering the latest results we show that DDQN with K-FAC learns more quickly than with other optimizers and improves constantly in contradiction to similar with Adam or RMSProp.

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https://doi.org/10.1007/978-981-10-7697-8 network architectures: recurrent and convolutional, as well as simpler feedforward networks. Classification accuracy was evaluated for different architectures, text representations and sets of miscellaneous parameters.

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