Local and Superlinear Convergence for Truncated Projections Methods
Least change secant updates can be obtained as the limit of iterated projections based on other secant updates. We show that these iterated projections can be terminated or truncated after any positive number of iterations and the local and the superlinear rate of convergence are still maintained. The truncated iterated projections method is used to find sparse and symmetric updates that are locally and superlinearly convergent.
Citable link to this pagehttps://hdl.handle.net/1911/101544
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- CAAM Technical Reports