Low-Rank plus Sparse Decomposition of Covariance Matrices using Neural Network Parametrization.
Michel BaesCalypso HerreraAriel NeufeldPierre RuyssenPublished in: CoRR (2019)
Keyphrases
- covariance matrices
- low rank
- tensor decomposition
- neural network
- low rank matrix
- rank minimization
- low rank matrices
- covariance matrix
- maximum likelihood
- convex optimization
- missing data
- linear combination
- singular value decomposition
- distance measure
- gaussian distribution
- regularized regression
- gaussian mixture model
- matrix factorization
- vector space
- matrix completion
- high order
- high dimensional data
- gaussian mixture
- linear classifiers
- semi supervised
- feature vectors
- kernel matrix
- pattern recognition
- sparse matrix
- sparse representation
- dimensionality reduction
- support vector
- image processing
- data sets