  By introducing a subsampling strategy, we propose a randomized block
Kaczmarz-Motzkin method for solving linear systems. Such strategy not only
determines the block size, but also combines and extends two famous strategies,
i.e., randomness and greed, and hence can inherit their advantages. Theoretical
analysis shows that the proposed method converges linearly in expectation to
the least-Euclidean-norm solution. Several numerical examples are reported to
verify the efficiency and feasibility of the new method.
