Zobrazeno 1 - 10
of 67
pro vyhledávání: '"Hongteng Xu"'
The COVID-19 vaccination decision-making preferences of elderly people: a discrete choice experiment
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-11 (2023)
Abstract COVID-19 is a continuing threat to global public health security. For elderly people, timely and effective vaccination reduces infection rates in this group and safeguards their health. This paper adopted an offline Discrete Choice Experimen
Externí odkaz:
https://doaj.org/article/c53365edbd6c460cb2fcb6b164497dd8
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. 45:7293-7307
Traditional multi-view learning methods often rely on two assumptions: ( i) the samples in different views are well-aligned, and ( ii) their representations obey the same distribution in a latent space. Unfortunately, these two assumptions may be que
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems. 34:1634-1638
Autor:
Xu Chen, Zhenlei Wang, Hongteng Xu, Jingsen Zhang, Yongfeng Zhang, Wayne Xin Zhao, Ji-Rong Wen
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. :1-14
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. 45:999-1016
We propose a new nonlinear factorization model for graphs that have topological structures, and optionally, node attributes. This model is based on a pseudo-metric called Gromov-Wasserstein (GW) discrepancy, which compares graphs in a relational way.
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. :1-17
Poster generation is a significant task for a wide range of applications, which is often time-consuming and requires lots of manual editing and artistic experience. In this paper, we propose a novel data-driven framework, called \textit{Text2Poster},
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1910c36a1ddb568b25224c1ebfa4780c
http://arxiv.org/abs/2301.02363
http://arxiv.org/abs/2301.02363
Publikováno v:
Proceedings of the 2023 SIAM International Conference on Data Mining (SDM) ISBN: 9781611977653
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4adbd859eee70d92e09dd2f9bb293cd5
https://doi.org/10.1137/1.9781611977653.ch52
https://doi.org/10.1137/1.9781611977653.ch52
Publikováno v:
Proceedings of the 31st ACM International Conference on Information & Knowledge Management.
Publikováno v:
Proceedings of the 31st ACM International Conference on Information & Knowledge Management.