Zobrazeno 1 - 10
of 131
pro vyhledávání: '"Xu, Haoyan"'
How can we train graph-based models to recognize unseen classes while keeping labeling costs low? Graph open-set learning (GOL) and out-of-distribution (OOD) detection aim to address this challenge by training models that can accurately classify know
Externí odkaz:
http://arxiv.org/abs/2410.16386
Autor:
Xu, Haoyan1 (AUTHOR), Zhang, Guangyao1 (AUTHOR), Wang, Wensheng1 (AUTHOR) xhaoyan58@gmail.com, Sun, Chenrui1 (AUTHOR), Wang, Hanyu1 (AUTHOR), Wu, Han1 (AUTHOR) whan@nefu.edu.cn, Sun, Zhuangzhi1 (AUTHOR) whan@nefu.edu.cn
Publikováno v:
Sensors (14248220). Oct2024, Vol. 24 Issue 19, p6197. 14p.
Publikováno v:
In ISA Transactions September 2024 152:96-112
Autor:
Duan, Ziheng, Xu, Haoyan, Wang, Yueyang, Huang, Yida, Ren, Anni, Xu, Zhongbin, Sun, Yizhou, Wang, Wei
With the advancement of sensing technology, multivariate time series classification (MTSC) has recently received considerable attention. Existing deep learning-based MTSC techniques, which mostly rely on convolutional or recurrent neural networks, ar
Externí odkaz:
http://arxiv.org/abs/2010.05649
Multivariate time series forecasting, which analyzes historical time series to predict future trends, can effectively help decision-making. Complex relations among variables in MTS, including static, dynamic, predictable, and latent relations, have m
Externí odkaz:
http://arxiv.org/abs/2008.08617
Multivariate time series forecasting is widely used in various fields. Reasonable prediction results can assist people in planning and decision-making, generate benefits and avoid risks. Normally, there are two characteristics of time series, that is
Externí odkaz:
http://arxiv.org/abs/2008.07730
We aim at solving the problem of predicting people's ideology, or political tendency. We estimate it by using Twitter data, and formalize it as a classification problem. Ideology-detection has long been a challenging yet important problem. Certain gr
Externí odkaz:
http://arxiv.org/abs/2006.01321
Autor:
Xu, Haoyan, Duan, Ziheng, Feng, Jie, Chen, Runjian, Zhang, Qianru, Xu, Zhongbin, Wang, Yueyang
Graph similarity computation aims to predict a similarity score between one pair of graphs to facilitate downstream applications, such as finding the most similar chemical compounds similar to a query compound or Fewshot 3D Action Recognition. Recent
Externí odkaz:
http://arxiv.org/abs/2005.08008
The ability to compute similarity scores between graphs based on metrics such as Graph Edit Distance (GED) is important in many real-world applications. Computing exact GED values is typically an NP-hard problem and traditional algorithms usually ach
Externí odkaz:
http://arxiv.org/abs/2005.07115
Multivariate time series (MTS) forecasting is an essential problem in many fields. Accurate forecasting results can effectively help decision-making. To date, many MTS forecasting methods have been proposed and widely applied. However, these methods
Externí odkaz:
http://arxiv.org/abs/2005.01185