%Aigaion2 BibTeX export from Bibliography database
%Saturday 02 May 2026 01:14:42 PM

@ARTICLE{,
            author = {Kopal, Jiř{\'{\i}} and Rozložn{\'{\i}}k, Miroslav and Tůma, Miroslav},
          keywords = {Approximate inverses, Gram–Schmidt orthogonalization, incomplete factorization, preconditioned iterative methods},
             title = {Factorized approximate inverses with adaptive dropping},
           journal = {SIAM Journal on Scientific Computing},
            volume = {38},
            number = {3},
              year = {2016},
             pages = {A1807–A1820},
               doi = {10.1137/15M1030315},
          abstract = {This paper presents a new approach to construct factorized approximate inverses for a symmetric and positive definite matrix A. The proposed strategy is based on adaptive dropping that reflects the quality of preserving the relation UZ = I between the direct factor U and the inverse factor Z satisfying A = UT U and A−1 = ZZT . An important part of the approach is column pivoting used to minimize the growth of the condition number of leading principal submatrices of U that occurs explicitly in the dropping criterion. Numerical experiments demonstrate that the resulting approximate inverse factorization is robust as a preconditioner for solving large and sparse systems of linear equations.},
  Preprint project = {NCMM},
     Preprint year = {2016},
   Preprint number = {02},
       Preprint ID = {NCMM/2016/02}
}