Near Linear Lower Bound for Dimension Reduction in L1.
Alexandr AndoniMoses CharikarOfer NeimanHuy L. NguyenPublished in: FOCS (2011)
Keyphrases
- dimension reduction
- lower bound
- feature extraction
- high dimensional
- principal component analysis
- upper bound
- low dimensional
- random projections
- linear discriminant analysis
- high dimensional problems
- singular value decomposition
- data mining and machine learning
- feature selection
- nonlinear manifold
- discriminative information
- feature space
- high dimensional data
- high dimensionality
- variable selection
- objective function
- manifold learning
- cluster analysis
- unsupervised learning
- dimensionality reduction
- high dimensional data analysis
- data mining
- qr decomposition
- feature vectors
- dimension reduction methods
- sparse metric learning