Sparse Reduced Rank Regression With Nonconvex Regularization.
Ziping ZhaoDaniel P. PalomarPublished in: CoRR (2018)
Keyphrases
- sparsity regularization
- sparse bayesian learning
- sparse regression
- mixed norm
- low rank matrices
- reproducing kernel hilbert space
- structured sparsity
- elastic net
- kernel ridge regression
- image restoration and reconstruction
- regression model
- rank minimization
- linear regression
- kernel matrices
- sparse approximation
- relevance vector machine
- canonical correlation analysis
- robust principal component analysis
- group lasso
- objective function
- sparsity inducing
- regression algorithm
- nonlinear programming
- support vector
- sparse coding
- convex optimization
- gaussian processes
- regression problems
- partial least squares
- regularization methods
- regularization parameter
- gaussian process
- model selection
- sparse kernel
- low rank
- low rank approximation
- gaussian process regression
- markov random field
- sparse representation
- kernel methods
- prior information
- regularized least squares
- support vector regression
- gradient boosting
- data dependent
- covariance function