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Yuyan Zheng, Jianhua Qu and Jiajia Yang
Similarity measures in heterogeneous information networks (HINs) have become increasingly important in recent years. Most measures in such networks are based on the meta path, a relation sequence connecting object types. However, in real-world scenarios,...
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Jiawei Han, Qingsa Li, Ying Xu, Yan Zhu and Bingxin Wu
Artificial intelligence-generated content (AIGC) technology has had disruptive results in AI, representing a new trend in research and application and promoting a new era of AI. The potential benefits of this technology are both profound and diverse. How...
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Konstantin Gaipov, Daniil Tausnev, Sergey Khodenkov, Natalya Shepeta, Dmitry Malyshev, Aleksey Popov and Lev Kazakovtsev
Rapid growth in the volume of transmitted information has lead to the emergence of new wireless networking technologies with variable heterogeneous topologies. With limited radio frequency resources, optimal routing problems arise, both at the network de...
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Jiahui Zhao, Zhibin Li, Pan Liu, Mingye Zhang
Pág. 115 - 142
Demand prediction plays a critical role in traffic research. The key challenge of traffic demand prediction lies in modeling the complex spatial dependencies and temporal dynamics. However, there is no mature and widely accepted concept to support the so...
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Mojtaba Nayyeri, Modjtaba Rouhani, Hadi Sadoghi Yazdi, Marko M. Mäkelä, Alaleh Maskooki and Yury Nikulin
One of the main disadvantages of the traditional mean square error (MSE)-based constructive networks is their poor performance in the presence of non-Gaussian noises. In this paper, we propose a new incremental constructive network based on the correntro...
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