UTV Expansin pack: Special-purpose rank-revealing algorithms This collection of Matlab 7.0 software supplements and complements the package UTV Tools from 1999, and includes implementations of special-purpose rank-revealing algorithms developed since the publication of the original package. We provide algorithms for computing and modifying symmetric rank-revealing VSV decompositions, we expand the algorithms for the ULLV decomposition of a matrix pair to handle interference-type problems with a rank-deficient covariance matrix, and we provide a robust and reliable Lanczos algorithm which -- despite its simplicity is -- able to capture all the dominant singular values of a sparse or structured matrix. These new algorithms have applications in signal processing, optimization and LSI information retrieval. (Source: http://plato.asu.edu)

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  1. Adcock, Ben; Huybrechs, Daan: Approximating smooth, multivariate functions on irregular domains (2020)
  2. Chang, Xiao-Wen; Kang, Peng; Titley-Peloquin, David: Error bounds for computed least squares estimators (2020)
  3. Fung, Samy Wu; Tyrväinen, Sanna; Ruthotto, Lars; Haber, Eldad: ADMM-softmax: an ADMM approach for multinomial logistic regression (2020)
  4. Jia, Zhongxiao: Approximation accuracy of the Krylov subspaces for linear discrete ill-posed problems (2020)
  5. Mohammady, Somaieh; Eslahchi, M. R.: Extension of Tikhonov regularization method using linear fractional programming (2020)
  6. Reichel, Lothar; Sadok, Hassane; Zhang, Wei-Hong: Simple stopping criteria for the LSQR method applied to discrete ill-posed problems (2020)
  7. Zare, Hossein; Hajarian, Masoud: Determination of regularization parameter via solving a multi-objective optimization problem (2020)
  8. Asl, Nazdar Abdollahi; Rostamy, Davood: Identifying an unknown time-dependent boundary source in time-fractional diffusion equation with a non-local boundary condition (2019)
  9. Bao, Jifeng; Yu, Carisa Kwok Wai; Wang, Jinhua; Hu, Yaohua; Yao, Jen-Chih: Modified inexact Levenberg-Marquardt methods for solving nonlinear least squares problems (2019)
  10. Buranay, Suzan C.; Iyikal, Ovgu C.: Approximate Schur-block ILU preconditioners for regularized solution of discrete ill-posed problems (2019)
  11. Cao, Zhifu; Fei, Qingguo; Jiang, Dong; Wu, Shaoqing; Fan, Zhiruo: Model updating of a stitched sandwich panel based on multistage parameter selection (2019)
  12. Caruso, Noe Angelo; Novati, Paolo: Convergence analysis of LSQR for compact operator equations (2019)
  13. Chung, Matthias; Binois, Mickaël; Gramacy, Robert B.; Bardsley, Johnathan M.; Moquin, David J.; Smith, Amanda P.; Smith, Amber M.: Parameter and uncertainty estimation for dynamical systems using surrogate stochastic processes (2019)
  14. Huybrechs, Daan; Olteanu, Anda-Elena: An oversampled collocation approach of the wave based method for Helmholtz problems (2019)
  15. Jozi, Meisam; Karimi, Saeed; Salkuyeh, Davod Khojasteh: An iterative method to compute minimum norm solutions of ill-posed problems in Hilbert spaces (2019)
  16. Kabashima, Kenta; Wu, Tianxiong; Nara, Takaaki: Reconstruction of current dipoles based on tensor decomposition of multipole coefficients (2019)
  17. Kaltenbacher, Barbara; Rundell, William: Regularization of a backwards parabolic equation by fractional operators (2019)
  18. Kerkri, Abdelmounaim; Allal, Jelloul; Zarrouk, Zoubir: The L-curve criterion as a model selection tool in PLS regression (2019)
  19. Mang, Andreas; Gholami, Amir; Davatzikos, Christos; Biros, George: CLAIRE: a distributed-memory solver for constrained large deformation diffeomorphic image registration (2019)
  20. Martinsson, P. G.; Quintana-Ortí, G.; Heavner, N.: randUTV: a blocked randomized algorithm for computing a rank-revealing UTV factorization (2019)

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