Compressive Bayesian K-SVD

Matteo Testa, Enrico Magli

Abstract: Highlights •A novel fully-automated compressive dictionary learning method is proposed.•All the parameters including the sparsity are estimated through Bayesian inference.•Our method achieves high performance at both signal recovery and classification.