Dimensionality reduction, regularization, and generalization in overparameterized regressions.
Ningyuan HuangDavid W. HoggSoledad VillarPublished in: CoRR (2020)
Keyphrases
- dimensionality reduction
- high dimensionality
- data representation
- low dimensional
- high dimensional data
- pattern recognition and machine learning
- feature selection
- high dimensional
- structure preserving
- feature extraction
- pattern recognition
- feature space
- principal component analysis
- linear model
- input space
- random projections
- manifold learning
- prior information
- learning machines
- metric learning
- regularization parameter
- kernel pca
- locally linear embedding
- regularization framework
- inductive bias
- sparse representation
- linear dimensionality reduction
- active learning
- involving high dimensional data