Titlebook: Secure Data Management; VLDB 2004 Workshop, Willem Jonker,Milan Petković Conference proceedings 2004 Springer-Verlag Berlin Heidelberg 200

Metastasis

Stanley R. M. Oliveira,Osmar R. Zaïaneed with traditional Q-Learning updates. The algorithm learns a latent-space that represents good policies with state clusters for options. We show that the DVQN algorithm is a promising approach for identifying initiation and termination conditions for option-based reinforcement learning. Experiment

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Bo Luo,Dongwon Lee,Wang-Chien Lee,Peng Liuystem configuration..Currently, there is no unified methodology which would summarize the best practices for developing such a system. This paper provides a list of system requirements for software-defined IoT networks for critical infrastructure. This list is one of the key phases in every system d

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Hai Yu,Ee-Peng Limmpared with the state-of-the-art methods like AlexNet, Squeeze Net, and Fire Detection Model. The proposed method is achieved an accuracy of 92.33% on an open-source dataset named ‘DeepQuestAI’. As the proposed CNN is very simple and straight forward, due to simplicity and a smaller number of layers

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