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Zengyu Cai, Chunchen Tan, Jianwei Zhang, Liang Zhu and Yuan Feng
As network technology continues to develop, the popularity of various intelligent terminals has accelerated, leading to a rapid growth in the scale of wireless network traffic. This growth has resulted in significant pressure on resource consumption and ...
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Yifei Wang, Shiyang Chen, Guobin Chen, Ethan Shurberg, Hang Liu and Pengyu Hong
This work considers the task of representation learning on the attributed relational graph (ARG). Both the nodes and edges in an ARG are associated with attributes/features allowing ARGs to encode rich structural information widely observed in real appli...
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Christos Bormpotsis, Mohamed Sedky and Asma Patel
In the realm of foreign exchange (Forex) market predictions, Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) have been commonly employed. However, these models often exhibit instability due to vulnerability to data perturbations...
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Joshua H. Tyler, Mohamed K. M. Fadul and Donald R. Reising
Initially introduced almost thirty years ago for the express purpose of providing electronic warfare systems the capabilities to detect, characterize, and identify radar emitters, Specific Emitter Identification (SEI) has recently received a lot of atten...
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Jesus Rodrigo Cedeno Jimenez, Angelly de Jesus Pugliese Viloria and Maria Antonia Brovelli
Environmental and health deterioration due to the increasing presence of air pollutants is a pressing topic for governments and organizations. Institutions such as the European Environment Agency have determined that more than 350,000 premature deaths ca...
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Zhihao Guo, Shengyuan Chen, Xiao Huang, Zhiqiang Qian, Chunsing Yu, Yan Xu and Fang Ding
Most machine-learning algorithms assume that instances are independent of each other. This does not hold for networked data. Node representation learning (NRL) aims to learn low-dimensional vectors to represent nodes in a network, such that all actionabl...
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Hedia Zardi, Hanen Karamti, Walid Karamti and Norah Saleh Alghamdi
Anomaly detection in online social networks (OSNs) is an important data mining task that aims to detect unexpected and suspicious users. To enhance anomaly exploration, anomaly ranking is used to assess the degree of user anomaly rather than applying bin...
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Nariman Adel Hussein, Hoda M. O. Mokhtar and Mohamed E. El-Sharkawi
Community search is a basic problem in graph analysis. In many applications, network nodes have certain properties that are important for the community to make sense of the application; hence, attributes are associated with nodes to capture their propert...
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Zhaoyang Liu, Renxiang Guan, Jingyu Hu, Weitao Chen and Xianju Li
Classification of remote sensing scene image (RSSI) has been broadly applied and has attracted increasing attention. However, scene classification methods based on convolutional neural networks (CNNs) require a large number of manually labeled samples as...
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Fabio Vittorio De Blasio
Mars has held large amounts of running and standing water throughout its history, as evidenced by numerous morphologies attributed to rivers, outflow channels, lakes, and possibly an ocean. This work examines the crater Antoniadi located in the Syrtis Ma...
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