Lossless Dimension Expanders Via Linearized Polynomials and Subspace Designs.
Venkatesan GuruswamiNicolas ReschChaoping XingPublished in: Comb. (2021)
Keyphrases
- dimensionality reduction
- low dimensional
- image compression
- kalman filter
- feature space
- high dimensional data
- subspace learning
- data sets
- feature extraction
- subspace methods
- kernel based nonlinear
- multiple dimensions
- arbitrary dimension
- low order
- lower dimensional
- subspace clustering
- high dimensional
- principal components
- principal components analysis
- principal component analysis
- multiresolution
- image sequences
- neural network