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Kai Zhang, Fei Zhao, Shoushan Luo, Yang Xin, Hongliang Zhu and Yuling Chen
With the development of intrusion detection, a number of the intelligence algorithms (e.g., artificial neural networks) are introduced to enhance the performance of the intrusion detection systems. However, many intelligence algorithms should be trained ...
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Bin Liu, Zhexi Zhang, Junchi Yan, Ning Zhang, Hongyuan Zha, Guofu Li, Yanting Li and Quan Yu
Risk control has always been a major challenge in finance. Overdue repayment is a frequently encountered discreditable behavior in online lending. Motivated by the powerful capabilities of deep neural networks, we propose a fusion deep learning approach,...
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Ren-Hung Hwang, Min-Chun Peng, Van-Linh Nguyen and Yu-Lun Chang
Recently, deep learning has been successfully applied to network security assessments and intrusion detection systems (IDSs) with various breakthroughs such as using Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) to classify malici...
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Sardar Parhat, Mijit Ablimit and Askar Hamdulla
In this paper, based on the multilingual morphological analyzer, we researched the similar low-resource languages, Uyghur and Kazakh, short text classification. Generally, the online linguistic resources of these languages are noisy. So a preprocessing i...
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