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pro vyhledávání: '"Chin, Jin Yao"'
Autor:
Guo, Wei, Wang, Hao, Zhang, Luankang, Chin, Jin Yao, Liu, Zhongzhou, Cheng, Kai, Pan, Qiushi, Lee, Yi Quan, Xue, Wanqi, Shen, Tingjia, Song, Kenan, Wang, Kefan, Xie, Wenjia, Ye, Yuyang, Guo, Huifeng, Liu, Yong, Lian, Defu, Tang, Ruiming, Chen, Enhong
Recommendation systems are essential for filtering data and retrieving relevant information across various applications. Recent advancements have seen these systems incorporate increasingly large embedding tables, scaling up to tens of terabytes for
Externí odkaz:
http://arxiv.org/abs/2412.00714
Autor:
Shen, Tingjia, Wang, Hao, Wu, Chuhan, Chin, Jin Yao, Guo, Wei, Liu, Yong, Guo, Huifeng, Lian, Defu, Tang, Ruiming, Chen, Enhong
Sequential Recommendation (SR) plays a critical role in predicting users' sequential preferences. Despite its growing prominence in various industries, the increasing scale of SR models incurs substantial computational costs and unpredictability, cha
Externí odkaz:
http://arxiv.org/abs/2412.00430
Autor:
Chin, Jin Yao1 s160005@ntu.edu.sg, Bhowmick, Sourav S.1 assourav@ntu.edu.sg, Jatowt, Adam2 adam@dl.kuis.kyoto-u.ac.jp
Publikováno v:
Journal of the Association for Information Science & Technology. Jun2019, Vol. 70 Issue 6, p547-562. 16p. 4 Color Photographs, 1 Black and White Photograph, 3 Diagrams, 7 Charts, 1 Graph.
Akademický článek
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