Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Qi Tan"'
Publikováno v:
Neurocomputing. 458:701-713
Infectious disease data, recording the numbers of infection cases in different locations and time, is one of the most typical categories of spatio-temporal data and plays an important role in the infectious disease control and prevention. However, du
Autor:
Tang Lihua, Rui-Heng Yang, Jun-Jun Shang, Yan Li, Xiang-Sheng Tao, Qi Tan, Ying Song, Li Chuanhua, Wei-Hua Huang, Wu Yingying, Dapeng Bao
Publikováno v:
International Journal of Medicinal Mushrooms. 21:1223-1239
Large numbers of DNA sequences deposited in the International Nucleotide Sequence Databases (INSD) are erroneously annotated. The erroneous information may lead to misleading conclusions or cause great economic losses to farmers. Lentinus edodes (= L
Publikováno v:
International Journal of Data Science and Analytics. 9:375-387
Diffusion processes over networks are widely encountered in various real-world applications. In many scenarios, however, only the states of nodes can be observed while the underlying diffusion networks are unknown. Many methods have therefore been pr
Autor:
Lloyd Tan, Mei Chin Lim, John S. Kuo, Clement Yong, Rebecca Harrison, Bryce W.Q. Tan, Hong Qi Tan, Shelli R. Kesler
Publikováno v:
Neuro Oncol
BACKGROUND Radiomics and connectome analysis are distinct and non-invasive methods of deriving biologic information from MRI. Radiomics analyzes features intrinsic to the tumor, and connectomics incorporates data regarding the tumor and surrounding n
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5814f132b80105ea636a7d1f6ab2c2e8
https://europepmc.org/articles/PMC7651490/
https://europepmc.org/articles/PMC7651490/
Deep learning has achieved incredible success over the past years, especially in various challenging predictive spatio-temporal analytics (PSTA) tasks, such as disease prediction, climate forecast, and traffic prediction, where intrinsic dependency r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2fbc4f215a7ea20392e5eaab9830b7a1
http://arxiv.org/abs/2009.06304
http://arxiv.org/abs/2009.06304
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030594909
ISMIS
ISMIS
Predictive spatio-temporal analytics aims to analyze and model the data with both spatial and temporal attributes for future forecasting. Among various models proposed for predictive spatio-temporal analytics, the recurrent neural network (RNN) has b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e484b2199d0fd6eb9e096b84c2a7fc56
https://doi.org/10.1007/978-3-030-59491-6_16
https://doi.org/10.1007/978-3-030-59491-6_16
A novel framework of graph Bayesian optimization and its applications to real-world network analysis
Publikováno v:
Expert Systems with Applications. 170:114524
Network structure optimization is a fundamental task of many expert and intelligent systems, such as the intelligent tools for chemical molecular discovery and expert systems for road network design. However, traditional model-free methods suffer fro
Publikováno v:
Knowledge and Information Systems. 55:671-694
Motivated by real applications, heterogeneous learning has emerged as an important research area, which aims to model the coexistence of multiple types of heterogeneity. In this paper, we propose a heterogeneous representation learning model with str
Publikováno v:
KDD
In this paper, we propose Task-Adversarial co-Generative Nets (TAGN) for learning from multiple tasks. It aims to address the two fundamental issues of multi-task learning, i.e., domain shift and limited labeled data, in a principled way. To this end
Publikováno v:
INFOCOM
Due to the explosive growth of social network services, friendship inference has been widely adopted by Online Social Service Providers (OSSPs) for friend recommendation. The conventional techniques, however, have limitations in accuracy or scalabili