Few-Sample Feature Selection via Feature Manifold Learning.
David CohenTal ShnitzerYuval KlugerRonen TalmonPublished in: ICML (2023)
Keyphrases
- manifold learning
- feature selection
- dimensionality reduction
- feature extraction
- dimension reduction
- feature set
- low dimensional
- locality preserving projections
- feature subset
- semi supervised
- feature space
- high dimensional
- diffusion maps
- nonlinear dimensionality reduction
- discriminative features
- preprocessing step
- high dimensional data
- subspace learning
- head pose estimation
- manifold learning algorithm
- feature vectors
- geodesic distance
- image features
- sample size
- high dimensionality
- text classification
- model selection
- classification accuracy
- laplacian eigenmaps
- discriminant projection
- sparse representation
- preprocessing
- learning algorithm
- machine learning
- least squares
- pairwise
- riemannian manifolds
- manifold structure
- face recognition
- decision trees
- image processing
- low dimensional manifolds
- data mining
- neural network