Multi-view Sparse Laplacian Eigenmaps for nonlinear Spectral Feature Selection.
Gaurav SrivastavaMahesh JangidPublished in: CoRR (2023)
Keyphrases
- multi view
- laplacian eigenmaps
- kernel pca
- feature selection
- dimensionality reduction
- feature space
- manifold learning
- single view
- semi supervised
- kernel methods
- principal component analysis
- multiple views
- high dimensional
- feature extraction
- support vector machine
- d objects
- support vector
- sparse representation
- kernel function
- feature set
- range images
- three dimensional
- co training
- machine learning
- spectral analysis
- spectral clustering
- model selection
- classification accuracy
- sparse coding
- graph laplacian
- surface reconstruction
- high dimensionality
- linear discriminant analysis
- text classification
- training data
- visual hull
- data points
- unsupervised learning