Greedy double subspaces coordinate descent method via orthogonalization
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The coordinate descent method is an effective iterative method for solving large linear least-squares problems. In this paper, we construct an effective coordinate descent method which iteratively projects the estimate onto a solution space formed by two selected hyperplanes. Our methods may be regarded as a block version of coordinate descent method which incorporates greedy rules. The convergence analysis of this method is provided and numerical simulations also confirm the effectiveness of our new methods.
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