Finding a sparse vector in a subspace: Linear sparsity using alternating directions.
Qing QuJu SunJohn WrightPublished in: NIPS (2014)
Keyphrases
- high dimensional
- regularized regression
- sparse approximation
- sparse representation
- orthogonal matching pursuit
- sparse matrix
- low dimensional
- sparsity constraints
- high dimensional data
- linear combination
- linear subspace
- subspace clustering
- hilbert space
- dimensionality reduction
- mixed norm
- basis vectors
- compressive sensing
- sparse coding
- principal component analysis
- subspace learning
- low rank
- linearly independent
- transformation matrix
- dictionary learning
- sparse reconstruction
- low rank representation
- feature space
- weight vector
- group lasso
- rank minimization
- vector space