  The coordinate descent method is an effective iterative method for solving
large linear least-squares problems. In this paper, for the highly coherent
columns case, we construct an effective coordinate descent method which
iteratively projects the estimate onto a solution space formed by two greedily
selected hyperplanes via Gram-Schmidt orthogonalization. Our methods may be
regarded as a simple block version of coordinate descent method which involves
two active columns. The convergence analysis of this method is provided and
numerical simulations also confirm the effectiveness for matrices with highly
coherent columns.
