Sparsity regularized Principal Component Pursuit.
Jing LiuPamela C. CosmanBhaskar D. RaoPublished in: ICASSP (2017)
Keyphrases
- principal components
- sparsity constraints
- principal component analysis
- sparse reconstruction
- multivariate data
- dimensionality reduction
- high dimensional
- sparsity inducing
- sparse representation
- mixed norm
- hyperplane
- least squares
- total least squares
- kernel space
- risk minimization
- neural network
- feature set
- principal component regression
- structured sparsity
- covariance matrix
- orthogonal matching pursuit
- correlation coefficient
- variable selection
- low dimensional
- image classification
- upper bound
- machine learning