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Creators/Authors contains: "Onisk, Lucas"

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  1. ; ; (, SIAM Journal on Imaging Sciences)
    Free, publicly-accessible full text available September 30, 2026
  2. ; ; ; ; (, Numerical Algorithms)
    Abstract Tikhonov regularization is commonly used in the solution of linear discrete ill-posed problems. It is known that iterated Tikhonov regularization often produces approximate solutions of higher quality than (standard) Tikhonov regularization. This paper discusses iterated Tikhonov regularization for large-scale problems with a general regularization matrix. Specifically, the original problem is reduced to small size by application of a fairly small number of steps of the Arnoldi or Golub-Kahan processes, and iterated Tikhonov is applied to the reduced problem. The regularization parameter is determined by using an extension of a technique first described by Donatelli and Hanke for quite special coefficient matrices. Convergence of the method is established and computed examples illustrate its performance. 
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    Free, publicly-accessible full text available May 6, 2026
  3. ; ; ; (, Numerical Algorithms)
    Free, publicly-accessible full text available January 10, 2026