2 papers
cs.LG2025
Deep greedy unfolding: Sorting out argsorting in greedy sparse recovery algorithms
Sina Mohammad-Taheri, Matthew J. Colbrook, Simone Brugiapaglia
Gradient-based learning imposes (deep) neural networks to be differentiable at all steps. This includes model-based architectures constructed by unrolling iterations of an iterativ…
cs.IT2025
The greedy side of the LASSO: New algorithms for weighted sparse recovery via loss function-based orthogonal matching pursuit
Sina Mohammad-Taheri, Simone Brugiapaglia
We propose a class of greedy algorithms for weighted sparse recovery by considering new loss function-based generalizations of Orthogonal Matching Pursuit (OMP). Given a (regulariz…