A novel low-rank hypergraph feature selection for multi-view classification.
Xiaohui ChengYonghua ZhuJingkuan SongGuoqiu WenWei HePublished in: Neurocomputing (2017)
Keyphrases
- multi view
- low rank
- feature selection
- semi supervised
- classification accuracy
- single view
- multiple views
- matrix factorization
- support vector
- convex optimization
- unsupervised learning
- text classification
- feature extraction
- d objects
- three dimensional
- high order
- model selection
- support vector machine
- depth map
- supervised learning
- feature space
- machine learning
- missing data
- singular value decomposition
- high dimensionality
- pairwise
- pattern recognition
- bundle adjustment
- feature set
- high dimensional data
- linear combination
- small number
- multi class
- training data
- training samples
- unlabeled data
- data sets
- dimensionality reduction
- knn
- object recognition
- decision trees
- computer vision
- light field
- view synthesis