… of labeled training data prevents us from performing parameter learning in a straightforward
way. Next, in a heterogeneous network, the information of different types of vertices and links …

… labeled influence maximization problem, which is to find a subset of nodes in a labeled social
network … In labeled social network, every node has a label, and every label has profit which …

… networks. Then paper proposes a forward some algorithms which build multi-dimension
networks, reduction dimension networks… add an edge between node1 and node2 labeled with a …

… labeling reference edge of two layers. Li and Brown [2] try to use smooth gradient prior
on reflection layer and sparse … According to the ghost phenomenon, they use deblurring-based …

… Using ghost edges for classification in sparsely labeled networks[C]// Proceedings of the
ACM SIGKDD 2008. New York: ACM Press, 2008: 256-264. [18] DASGUPTA K, SINGH R, …

… 本文引入Ghost 模块作为YOLOv5s 骨干网络模型, 减少压缩模型… 为在嵌入式设备上实现天牛
检测,在主干网络引入Ghost … the longhorn beetles at the edge using the deep learning YOLOv5s …

… ranging from citizen to “ghost worker,” to … using fake IDs in order to enter the labor market.
Traveling around China, especially in the urban corners or suburban factory-villages densely …

… Radar measurements of moving objects around corners in a realistic scene[C]. SPIE 9077,
Radar … Positioning of objects behind corners using X-band radar[C]. 2011 30th URSI General …

… Schematic diagram of the principle of real-space ghost … Schematic diagram of the principle
of phase ghost imaging[… Schematic diagram of the principle of diffraction ghost imaging[79] …

… bugs in such programs are subtle and difficult to find using testing or simulation. Thus it is
desirable to apply … task we use the keyword all to express all data objects in all scopes (local …