Multi-view manifold learning with locality alignment

@article{Zhao2018MultiviewML,
  title={Multi-view manifold learning with locality alignment},
  author={Yue Zhao and Xinge You and Shujian Yu and Chang Xu and Wei Yuan and Xiao-Yuan Jing and T. Zhang and D. Tao},
  journal={Pattern Recognit.},
  year={2018},
  volume={78},
  pages={154-166}
}
Abstract Manifold learning aims to discover the low dimensional space where the input high dimensional data are embedded by preserving the geometric structure. Unfortunately, almost all the existing manifold learning methods were proposed under single view scenario, and they cannot be straightforwardly applied to multiple feature sets. Although concatenating multiple views into a single feature provides a plausible solution, it remains a question on how to better explore the independence and… Expand
41 Citations
Manifold Alignment via Global and Local Structures Preserving PCA Framework
  • 5
  • PDF
Flexible Multi-View Unsupervised Graph Embedding
Multi-view Common Component Discriminant Analysis for Cross-view Classification
  • 18
  • PDF
Multiview Hybrid Embedding: A Divide-and-Conquer Approach
  • 8
  • PDF
Discriminant and Complementary Autoencoder Network for Multi-view Learning
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 61 REFERENCES
Bilevel Multiview Latent Space Learning
  • 8
  • PDF
Inductive manifold learning using structured support vector machine
  • 10
Learning representations from multiple manifolds
  • 17
  • PDF
Low-Rank Discriminant Embedding for Multiview Learning
  • 90
Unified subspace learning for incomplete and unlabeled multi-view data
  • 41
  • PDF
Large-Margin Predictive Latent Subspace Learning for Multiview Data Analysis
  • 83
  • PDF
A Survey on Multi-view Learning
  • 769
  • PDF
...
1
2
3
4
5
...