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Titlebook: Intelligent Systems and Applications; Proceedings of the 2 Kohei Arai Conference proceedings 2022 The Editor(s) (if applicable) and The Aut

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,Detecting and Fixing Nonidiomatic Snippets in Python Source Code with Deep Learning,mining the nonidiomatic pattern type is a classification problem, which we solve by training a feedforward neural network. We evaluate the process on a dataset containing more than 13 000 programs coded by students.
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Tensor Data Scattering and the Impossibility of Slicing Theorem,ded, which can effectively indicate the storage efficiency of sparse tensor and the possibility of parallelly using it. The source code, including CUDA code, is provided in a related open-source project.
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Scope and Sense of Explainability for AI-Systems,ch in retrospect were characterized as ingenious (for example move 37 of the game 2 of AlphaGo). It will be elaborated on arguments supporting the notion that if AI-solutions were to be discarded in advance because of their not being thoroughly comprehensible, a great deal of the potentiality of intelligent systems would be wasted.
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Machine Learning Based , Norm Minimization for Maglev Vibration Isolation Platform,n classical and modern control approaches. In this study, Q-Learning RL algorithm combined with analytic LMI method has been utilized to solve micro-scale vibration isolation problem as energy efficient as possible.
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Domain Generalization Using Ensemble Learning,spective, we build an ensemble model on top of base deep learning models trained on a single source to enhance the generalization of their collective prediction. The results achieved thus far have demonstrated promising improvements of the ensemble over any of its base learners.
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Reputation Analysis Based on Weakly-Supervised Bi-LSTM-Attention Network,introduced, which is helpful to capture the important information in the context and improve the accuracy of sentiment classification. Finally, we use TF-IDF and LDA topic models to mine the review topics and extract the consumers’ opinions on different sentiment polarities.
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