We present in this paper a biconvex reformulation of an L_2 − L_0 problem composed of a least-square data term plus a sparsity term introduced as a constraint or a penalization. Minimization algorithms are derived and compared with the state of the art in L_2 − L_0 minimization by relaxation or deep learning. Application results are shown on Single-Molecule Localization Microscopy.