Optimal Convex Lifted Sparse Phase Retrieval and PCA With an Atomic Matrix Norm Regularizer.
Andrew D. McRaeJustin RombergMark A. DavenportPublished in: IEEE Trans. Inf. Theory (2023)
Keyphrases
- robust principal component analysis
- low rank
- nuclear norm
- low rank matrices
- convex optimization
- low rank matrix
- principal component analysis
- low rank and sparse
- high dimensional
- singular value decomposition
- sparse matrix
- trace norm
- rank minimization
- sparse regression
- sparse pca
- covariance matrix
- total variation
- semi supervised
- semi infinite programming
- low rank approximation
- probabilistic inference
- sparse principal component analysis
- dimensionality reduction
- coefficient matrix
- convex hull
- singular values
- principal components analysis
- convex functions
- missing data
- group lasso
- information retrieval
- principal components
- piecewise linear
- matrix factorization
- random projections
- lp norm
- semidefinite
- canonical correlation analysis
- globally optimal
- regularization term
- graphical models
- feature space
- feature extraction