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Greta, GREediness: Theory and Algorithms, is a project funded by the French National Research Agency (ANR), with project code: GRETA 12-BS02-004-01.

Over the past few years, many problems of automatically computing sparse representations of data have been addressed through convex optimization formulations. This holds both for contributions in machine learning and signal processing. However, aiming at sparsity actually involves an l0 “norm” regularization/constraint, and the convex optimization way is essentially a proxy to achieve this sparsity – through the recourse to an l1 norm, which itself is a proxy to the l0. In this project, we want to set the focus on another way of dealing with the sparsity objective, which, to our opinion, has been neglected recently: greedy methods.