Dimension reduction of multimodal data by auto-weighted local discriminant analysis.
Rongxiu LuYingjie CaiJianyong ZhuFeiping NieHui YangPublished in: Neurocomputing (2021)
Keyphrases
- discriminant analysis
- dimension reduction
- linear discriminant analysis
- multimodal data
- high dimensional data analysis
- dimensionality reduction methods
- principal component analysis
- feature extraction
- dimensionality reduction
- face recognition
- supervised dimensionality reduction
- kernel trick
- cluster analysis
- similarity search
- high dimensional data
- fisher discriminant analysis
- scatter matrices
- multimedia databases
- feature space
- manifold learning
- support vector
- high dimensional
- partial least squares
- cross modal
- low dimensional
- random projections
- data sets
- support vector machine svm
- feature selection
- null space
- principal components analysis
- singular value decomposition
- unsupervised learning
- feature vectors
- neural network
- principal components
- preprocessing
- data analysis
- decision trees
- computer vision