There has been a significant interest in the recovery of low-rank matrices from an incomplete of measurements, due to both theoretical and practical developments demonstrating th...
S. Derin Babacan, Martin Luessi, Rafael Molina, Ag...
Recently, relevance vector machines (RVM) have been fashioned from a sparse Bayesian learning (SBL) framework to perform supervised learning using a weight prior that encourages s...
Traditional non-parametric statistical learning techniques are often computationally attractive, but lack the same generalization and model selection abilities as state-of-the-art...
Sparse image reconstruction is of interest in the fields of radioastronomy and molecular imaging. The observation is assumed to be a linear transformation of the image, and corrup...