Our paper entitled *Recovery and convergence rate of the Frank-Wolfe Algorithm for the m-EXACT-SPARSE Problem* by F. Cherfaoui, V. Emiya, L. Ralaivola and S. Anthoine has been accepted for a publication in the IEEE Transactions on Information Theory journal.

**Abstract** : We study the properties of the Frank-Wolfe
algorithm to solve the m-EXACT-SPARSE reconstruction problem, where a
signal y must be expressed as a sparse linear combination of a
predefined set of atoms, called dictionary. We prove that when the
dictionary is quasi-incoherent, then the iterative process implemented
by the Frank-Wolfe algorithm only recruits atoms from the support of the
signal, that is the smallest set of atoms from the dictionary that
allows for a perfect reconstruction of y. We also prove that when the
dictionary is quasi-incoherent, there exists an iteration beyond which
the algorithm converges exponentially.