Spectral Non-Convex Optimization for Dimension Reduction with Hilbert-Schmidt Independence Criterion.
Chieh WuJared MillerYale ChangMario SznaierJennifer G. DyPublished in: CoRR (2019)
Keyphrases
- convex optimization
- dimension reduction
- principal component analysis
- feature extraction
- singular value decomposition
- feature selection
- high dimensional
- linear discriminant analysis
- low rank
- feature space
- variable selection
- low dimensional
- dimensionality reduction
- total variation
- high dimensionality
- random projections
- cluster analysis
- high dimensional data
- unsupervised learning
- pairwise
- data sets
- support vector
- face recognition