Dimensionality Reduction, Regularization, and Generalization in Overparameterized Regressions.
Ningyuan Teresa HuangDavid W. HoggSoledad VillarPublished in: SIAM J. Math. Data Sci. (2022)
Keyphrases
- dimensionality reduction
- data representation
- principal component analysis
- high dimensional
- low dimensional
- high dimensionality
- feature extraction
- high dimensional data
- random projections
- feature space
- data points
- manifold learning
- principal components
- pattern recognition and machine learning
- structure preserving
- dimensionality reduction methods
- linear discriminant analysis
- pattern recognition
- metric learning
- regularization parameter
- regularization framework
- regularization methods
- feature selection
- singular value decomposition
- input space
- sparse representation
- factor analysis
- parameter selection
- kernel learning
- decision trees
- linear dimensionality reduction
- computer vision