Zobrazeno 1 - 10
of 293
pro vyhledávání: '"Chen, Wei Jie"'
Autor:
Li, Sheng-Wei, Wei, Zi-Xiang, Chen, Wei-Jie, Yu, Yi-Hsin, Yang, Chih-Yuan, Hsu, Jane Yung-jen
Existing zero-shot skeleton-based action recognition methods utilize projection networks to learn a shared latent space of skeleton features and semantic embeddings. The inherent imbalance in action recognition datasets, characterized by variable ske
Externí odkaz:
http://arxiv.org/abs/2407.13460
Publikováno v:
In Applied Soft Computing January 2025 169
Recent advance on linear support vector machine with the 0-1 soft margin loss ($L_{0/1}$-SVM) shows that the 0-1 loss problem can be solved directly. However, its theoretical and algorithmic requirements restrict us extending the linear solving frame
Externí odkaz:
http://arxiv.org/abs/2203.00399
Autor:
Qian, Bo, Li, Ting-Yu, Zheng, Zhao-Xuan, Zhang, Han-Yu, Xu, Wen-Qi, Mo, Su-Min, Cui, Jia-Jia, Chen, Wei-Jie, Lin, Yu-Chun, Lin, Zhong-Ning
Publikováno v:
In Journal of Hazardous Materials 5 July 2024 472
Publikováno v:
IEEE Transactions on Cybernetics, 2021
Cross-manifold clustering is a hard topic and many traditional clustering methods fail because of the cross-manifold structures. In this paper, we propose a Multiple Flat Projections Clustering (MFPC) to deal with cross-manifold clustering problems.
Externí odkaz:
http://arxiv.org/abs/2002.06739
Autor:
Pan, Xiu-wu, Chen, Wen-jin, Xu, Da, Guan, Wen-bin, Li, Lin, Chen, Jia-xin, Chen, Wei-jie, Dong, Ke-qin, Ye, Jian-qing, Gan, Si-shun, Zhou, Wang, Cui, Xin-gang
Publikováno v:
In iScience 15 December 2023 26(12)
Autor:
Chen, Wei Jie
University of Macau
Institute of Chinese Medical Sciences
Institute of Chinese Medical Sciences
Externí odkaz:
http://umaclib3.umac.mo/record=b3690953
Autor:
Chen, Wei-Jie1 (AUTHOR), Ko, I-Shih1 (AUTHOR), Lin, Chi-An1 (AUTHOR), Chen, Chun-Jen1 (AUTHOR), Wu, Jiun-Shian1 (AUTHOR), Chan, C. K.1 (AUTHOR) ckchan@gate.sinica.edu.tw
Publikováno v:
Entropy. Jan2024, Vol. 26 Issue 1, p13. 17p.
Autor:
Chen, Wei-Jie1 (AUTHOR), Gan, Chun-Xia1 (AUTHOR), Cai, Yang-Wei1 (AUTHOR), Liu, Yang-Yang2 (AUTHOR), Xiao, Pei-Lin1 (AUTHOR), Zou, Li-Li1 (AUTHOR), Xiong, Qing-Song1 (AUTHOR), Qin, Fang1 (AUTHOR), Tao, Xie-Xin1 (AUTHOR), Li, Ran1 (AUTHOR), Du, Hua-An1 (AUTHOR), Liu, Zeng-Zhang1 (AUTHOR), Yin, Yue-Hui1 (AUTHOR), Ling, Zhi-Yu1 (AUTHOR) lingzhiyu@cqmu.edu.cn
Publikováno v:
BMC Medicine. 11/23/2023, Vol. 21 Issue 1, p1-17. 17p.
Recent advances show that two-dimensional linear discriminant analysis (2DLDA) is a successful matrix based dimensionality reduction method. However, 2DLDA may encounter the singularity issue theoretically and the sensitivity to outliers. In this pap
Externí odkaz:
http://arxiv.org/abs/1801.07426