  The randomized sparse Kaczmarz method was recently proposed to recover sparse
solutions of linear systems. In this work, we introduce a greedy variant of the
randomized sparse Kaczmarz method by employing the sampling Kaczmarz-Motzkin
method, and prove its linear convergence in expectation with respect to the
Bregman distance in the noiseless and noisy cases. This greedy variant can be
viewed as a unification of the sampling Kaczmarz-Motzkin method and the
randomized sparse Kaczmarz method, and hence inherits the merits of these two
methods. Numerically, we report a couple of experimental results to demonstrate
its superiority
