Reference-based compressed sensing: A sample complexity approach.
João F. C. MotaLior WeizmanNikos DeligiannisYonina C. EldarMiguel R. D. RodriguesPublished in: ICASSP (2016)
Keyphrases
- compressed sensing
- sample complexity
- image reconstruction
- theoretical analysis
- learning problems
- learning algorithm
- upper bound
- random projections
- supervised learning
- sparse representation
- active learning
- special case
- natural images
- training examples
- generalization error
- lower bound
- small number
- machine learning algorithms
- object recognition
- signal processing
- semi supervised learning
- cross validation
- reinforcement learning
- similarity measure
- data mining