Sparse PCA through Low-rank Approximations.
Dimitris S. PapailiopoulosAlexandros G. DimakisStavros KorokythakisPublished in: ICML (3) (2013)
Keyphrases
- sparse pca
- low rank approximation
- kernel matrix
- semidefinite programming
- singular value decomposition
- principal component analysis
- subspace learning
- low rank
- feature selection
- spectral clustering
- latent semantic indexing
- anomaly detection
- iterative algorithms
- nonnegative matrix factorization
- principle component analysis
- kernel methods
- dimensionality reduction
- feature space
- kernel function
- object recognition
- machine learning
- model selection
- adjacency matrix
- metric learning
- least squares
- ls svm
- data analysis
- matrix factorization
- dimension reduction
- cluster analysis
- covariance matrix
- image segmentation
- missing data