An empirical-bayes approach to recovering linearly constrained non-negative sparse signals.
Jeremy P. VilaPhilip SchniterPublished in: CAMSAP (2013)
Keyphrases
- linearly constrained
- linear constraints
- signal reconstruction
- variational inequalities
- high dimensional
- signal processing
- positive and negative
- tensor factorization
- decision trees
- sparse representation
- compressive sensing
- sensitivity analysis
- independent component analysis
- sufficient conditions
- maximum likelihood
- multi agent systems
- support vector
- bayesian networks
- image processing