15 citations · 17 across the 2 of their papers we have counts for
2 papers
cs.LG2012★ 15 cited
Learning efficient sparse and low rank models
Pablo Sprechmann, Alex M. Bronstein, Guillermo Sapiro
Parsimony, including sparsity and low rank, has been shown to successfully model data in numerous machine learning and signal processing tasks. Traditionally, such modeling approac…
cs.CV2010★ 2 cited
Collaborative Sources Identification in Mixed Signals via Hierarchical Sparse Modeling
Pablo Sprechmann, Ignacio Ramirez, Pablo Cancela +1
A collaborative framework for detecting the different sources in mixed signals is presented in this paper. The approach is based on C-HiLasso, a convex collaborative hierarchical s…