Sparse sampling Kaczmarz–Motzkin method with linear convergence

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