In the dictionary learning (or sparse coding) problem, we are given a collection of signals (vectors in $\mathbb{R}^d$), and the goal is to find a "basis" in which the signals have a sparse (approximate) representation. The problem has received a lot of attention in signal processing, learning, and theoretical computer science... (read more)

PDF
Submit
results from this paper
to get state-of-the-art GitHub badges and help the
community compare results to other papers.