2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.LG2022★ 2 cited
CIMUFS: Complementary and Consensus Learning-based Incomplete Multi-view Unsupervised Feature Selection
Yanyong Huang, Zongxin Shen, Yuxin Cai +4
Multi-view unsupervised feature selection (MUFS) has been demonstrated as an effective technique to reduce the dimensionality of multi-view unlabeled data. The existing methods ass…
cs.LG2022
Incremental Unsupervised Feature Selection for Dynamic Incomplete Multi-view Data
Yanyong Huang, Kejun Guo, Xiuwen Yi +2
Multi-view unsupervised feature selection has been proven to be efficient in reducing the dimensionality of multi-view unlabeled data with high dimensions. The previous methods ass…
cs.LG2020★ 1 cited
Micro-supervised Disturbance Learning: A Perspective of Representation Probability Distribution
Jielei Chu, Jing Liu, Hongjun Wang +3
The instability is shown in the existing methods of representation learning based on Euclidean distance under a broad set of conditions. Furthermore, the scarcity and high cost of…