Sparse Bayesian learning (SBL) exploits sparse information from a Bayesian perspective by making sparse prior assumptions about the signal. It has good flexibility in modeling sparse signals and can ...

The multiplication of a sparse matrix with a dense vector (SpMV) is a key component in many numerical schemes and its performance is known to be severely limited by main memory access. Several ...