Cargando…
Semi-Supervised Multi-View Clustering with Weighted Anchor Graph Embedding
A number of literature reports have shown that multi-view clustering can acquire a better performance on complete multi-view data. However, real-world data usually suffers from missing some samples in each view and has a small number of labeled samples. Additionally, almost all existing multi-view c...
Autores principales: | Wang, Senhong, Cao, Jiangzhong, Lei, Fangyuan, Dai, Qingyun, Liang, Shangsong, Wing-Kuen Ling, Bingo |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8331271/ https://www.ncbi.nlm.nih.gov/pubmed/34354743 http://dx.doi.org/10.1155/2021/4296247 |
Ejemplares similares
-
Hybrid Low-Order and Higher-Order Graph Convolutional Networks
por: Lei, Fangyuan, et al.
Publicado: (2020) -
Deep Learning-Based Synthesized View Quality Enhancement with DIBR Distortion Mask Prediction Using Synthetic Images
por: Zhang, Huan, et al.
Publicado: (2022) -
Person re-identification via semi-supervised adaptive graph embedding
por: Liu, Jiao, et al.
Publicado: (2022) -
Semi-Supervised Learning in Medical Images Through Graph-Embedded Random Forest
por: Gu, Lin, et al.
Publicado: (2020) -
Zero-Shot Neural Decoding with Semi-Supervised Multi-View Embedding
por: Akamatsu, Yusuke, et al.
Publicado: (2023)