PUBLICATIONS SINCE 2001

 

 
The files for the publications made available below may differ slightly 
from the files for the final versions published in journals and proceedings.
 

Recent Publications

• H. Alqahtani, C. F. Borges, D. Lj. Djukic', R. M. Mutavdzic' Djukic', L. Reichel, and M. M. Spalevic'
  Computation of pairs of related Gauss-type quadrature rules
  Appl. Numer. Math., in press
  pdf file

• H. Almutairi, D. Lj. Djukic', R. M. Mutavdzic' Djukic', M. S. Pranic', L. Reichel, and M. M. Spalevic'
  Enhanced averaged quadrature rules with application to error estimation
  in Analysis, Approximation, Optimization: Computation and Applications, eds. M. Stanic', M. Albijanic', D. Djurcic', and M. M. Spalevic', Springer, in press
  pdf file

• A. Buccini, F. Chen, O. De la Cruz Cabrera, and L. Reichel
  Fast alternating fitting methods for trigonometric curves for large data sets
  Appl. Numer. Math., in press
  pdf file

• O. De la Cruz Cabrera, J. Jin, and L. Reichel
  Sparse approximation of complex networks
  Appl. Numer. Math., in press
  pdf file

• C. Fenu, L. Reichel, G. Rodriguez, and Y. Zhang
  Weighted chained graphs with some applications
  Appl. Numer. Math., in press
  pdf file

Ill-Posed Problems

• A. Buccini, O. De la Cruz Cabrera, C. Koukouvinos, M. Mitrouli, and L. Reichel
  Variable selection in saturated and supersaturated designs via l_p-l_q minimization
  Commun. Statist. Simulation Comput., 52 (2023), pp. 4326-4347
  pdf file

• L. Onisk, L. Reichel, and H. Sadok
  Numerical considerations of block GMRES methods when applied to linear discrete ill-posed problems
  J. Comput. Appl. Math., 430 (2023), Art. 115262
  pdf file

• A. Buccini and L. Reichel
  Limited memory restarted l^p-l^q minimization methods using generalized Krylov subspaces
  Adv. Comput. Math., 49 (2023), Art. 26
  pdf file

• T. Mach, L. Reichel, and M. Van Barel
  Adaptive cross approximation for Tikhonov regularization in general form
  Numer. Algorithms, 92 (2023), pp. 815-830
  pdf file

• A. Buccini, L. Onisk, and L. Reichel
  An Arnoldi-based preconditioner for iterated Tikhonov regularization
  Numer. Algorithms, 92 (2023), pp. 223-245
  pdf file

• M. Alkilayh and L. Reichel
  Some numerical aspects of Arnoldi-Tikhonov regularization
  Appl. Numer. Math., 185 (2023), pp. 503-515
  pdf file

• A. Alqahtani, R. Ramlau, and L. Reichel
  Error estimates for Golub–Kahan bidiagonalization with Tikhonov regularization for ill–posed operator equations
  Inverse Problems, 39 (2023), Art. 025002
  pdf file

• A. Buccini, M. Donatelli, and L. Reichel
  Theoretical and numerical aspects of a non-stationary preconditioned iterative method for linear discrete ill-posed problems
  J. Comput. Appl. Math., 423 (2023), Art. 114940
  pdf file

• M. Alotaibi, A. Buccini, and L. Reichel
  Krylov subspace split Bregman methods
  Appl. Numer. Math., 184 (2023), pp. 371-390
  pdf file

• A. Alqahtani, T. Mach, and L. Reichel
  Tikhonov regularization in general form with Chebfun
  Proc. Appl. Math. Mech., 22 (2022), Art. e202200041
  pdf file

• A. Buccini, M. Pragliola, L. Reichel, and F. Sgallari
  A comparison of parameter choice rules for l_p-l_q minimization
  An. Univ. di Ferrara, 68 (2022), pp. 441-463
  pdf file

• L. Reichel and U. O. Ugwu
  Weighted tensor Golub-Kahan-Tikhonov-type methods applied to image processing using a t-product
  J. Comput. Appl. Math., 415 (2022), Art. 114488
  pdf file

• L. Reichel and U. O. Ugwu
  Tensor Arnoldi-Tikhonov and GMRES-type methods for ill-posed problems with a t-product structure
  J. Sci. Comput., 90 (2022), Art. 59
  pdf file

• L. Reichel and U. O. Ugwu
  The tensor Golub-Kahan-Tikhonov method applied to the solution of ill-posed problems with a t-product structure
  Numer. Linear Algebra Appl., 29 (2022), e2412
  pdf file

• M. Alotaibi, A. Buccini, and L. Reichel
  Restoration of blurred images corrupted by impulse noise via median filters and l_p-l_q minimization
  Proc. 21st Intern. Conf. Comput. Sci. Appl. (ICCSA), Cagliari, Italy, 2021, pp. 112-122. Publisher: IEEE, doi: 10.1109/ICCSA54496.2021.00025
  pdf file

• X. Bai, A. Buccini, and L. Reichel
  Solution of linear discrete ill-posed problems by discretized Chebyshev expansion
  Proc. 21st Intern. Conf. Comput. Sci. Appl. (ICCSA), Cagliari, Italy, 2021, pp. 101-111. Publisher: IEEE, doi: 10.1109/ICCSA54496.2021.00024
  pdf file

• A. Buccini and L. Reichel
  Generalized cross validation for l_p-l_q minimization
  Numer. Algorithms, 88 (2021), pp. 1595-1616
  pdf file

• X. Bai, A. Buccini, and L. Reichel
  Golub-Kahan vs. Monte Carlo: A comparison of bidiagonlization and a randomized SVD method for the solution of linear discrete ill-posed problems
  BIT Numer. Math., 61 (2021), pp. 1093-1114
  pdf file

• A. Alqahtani, S. Gazzola, L. Reichel, and G. Rodriguez
  On the block Lanczos and block Golub-Kahan reduction methods applied to discrete ill-posed problems
  Numer. Linear Algebra Appl., 28 (2021), e2376
  pdf file

• A. Buccini, M. Pasha, and L. Reichel
  Linearized Krylov subspace Bregman iteration with nonnegativity constraint
  Numer. Algorithms, 87 (2021), pp. 1177-1200
  pdf file

• L. Reichel and U. O. Ugwu
  Tensor Krylov subspace methods with an invertible linear transform product applied to image processing
  Appl. Numer. Math., 166 (2021), pp. 186-207
  pdf file

• A. Buccini, M. Donatelli, L. Reichel, and W. Zhang
  A new nonstationary preconditioned iterative method for linear discrete ill-posed problems with application to image deblurring
  Numer. Linear Algebra Appl., 28 (2021), e2353
  pdf file

• A. Buccini, G. Huang, L. Reichel, and F. Yin
  On the choice of regularization matrix for an l_2-l_q minimization method for image restoration
  Appl. Numer. Math., 164 (2021), pp. 211-221
  pdf file

• X. Bai, G. Huang, X.-J. Lei, L. Reichel, and F. Yin
  A novel modified TRSVD method for large-scale linear discrete ill-posed problems
  Appl. Numer. Math., 164 (2021), pp. 72-88
  pdf file

• L. Dykes, R. Ramlau, L. Reichel, K. Soodhalter, and R. Wagner
  Lanczos-based fast blind deconvolution methods
  J. Comput. Appl. Math., 382 (2021), Art. 113067
  pdf file

• A. Buccini, M. Pasha, and L. Reichel
  Modulus-based iterative methods for constrained l_p-l_q minimization
  Inverse Problems, 36 (2020), Art. 084001
  pdf file

• A. Buccini, O. De la Cruz Cabrera, M. Donatelli, A. Martinelli, and L. Reichel
  Large-scale regression with non-convex loss and penalty
  Appl. Numer. Math., 157 (2020), pp. 590-601
  pdf file

• F. P. A. Beik, K. Jbilou, M. Najafi-Kalyani, and L. Reichel
  Golub-Kahan bidiagonalization for ill-conditioned tensor equations with applications
  Numer. Algorithms, 84 (2020), pp. 1535-1563
  pdf file

• L. Reichel, H. Sadok, and W. Zhang
  Simple stopping criteria for the LSQR method applied to discrete ill-posed problems
  Numer. Algorithms, 84 (2020), pp. 1381-1395
  pdf file

• A. Buccini and L. Reichel
  An l_p-l_q minimization method with cross-validation for the restoration of impulse noise contaminated images
  J. Comput. Appl. Math., 375 (2020), Art. 112824
  pdf file

• A. Buccini, M. Pasha, and L. Reichel
  Generalized singular value decomposition with iterated Tikhonov regularization
  J. Comput. Appl. Math., 373 (2020), Art. 112276
  pdf file

• A. Buccini, Y. Park, and L. Reichel
  Comparison of a-posteriori parameter choice rules for linear discrete ill-posed problems
  J. Comput. Appl. Math., 373 (2020), Art. 112138
  pdf file

• F. P. A. Beik, M. Najafi-Kalyani, and L. Reichel
  Iterative Tikhonov regularization of tensor equations based on the Arnoldi process and some of its generalizations
  Appl. Numer. Math., 151 (2020), pp. 425-447
  pdf file

• P. Dell'Acqua, M. Donatelli, and L. Reichel
  Non-stationary structure-preserving preconditioning for image restoration
  in Computational Methods for Inverse Problems in Imaging, eds. M. Donatelli and S. Serra-Capizzano, Springer, Cham, 2019, pp. 51-75
  pdf file

• A. Buccini and L. Reichel
  An l_2-l_q regularization method for large discrete ill-posed problems
  J. Sci. Comput., 78 (2019), pp. 1526-1549
  pdf file

• G. Huang, L. Reichel, and F. Yin
  On the choice of subspace for large-scale Tikhonov regularization problems in general form
  Numer. Algorithms, 81 (2019), pp. 33-55
  pdf file

• R. Ramlau and L. Reichel
  Error estimates for Arnoldi-Tikhonov regularization for ill-posed operator equations
  Inverse Problems, 35 (2019), Art. 055002
  pdf file

• S. Gazzola, S. Noschese, P. Novati, and L. Reichel
  Arnoldi decomposition, GMRES, and preconditioning for linear discrete ill-posed problems
  Appl. Numer. Math., 142 (2019), pp. 102-121
  pdf file

• A. H. Bentbib, M. El Guide, K. Jbilou, E. Onunwor, and L. Reichel
  Solution methods for linear discrete ill-posed problems for color image restoration
  BIT, 58 (2018), pp. 555-578
  pdf file

• L. Dykes, G. Huang, S. Noschese, and L. Reichel
  Regularization matrices for discrete ill-posed problems in several space-dimensions
  Numer. Linear Algebra Appl., 25 (2018), e2163 (16 pages)
  pdf file

• A. Buccini, Y. Park, and L. Reichel
  Numerical aspects of the nonstationary modified linearized Bregman algorithm
  Appl. Math. Comput., 337 (2018), pp. 386-398
  pdf file

• Y. Park, L. Reichel, G. Rodriguez, and X. Yu
  Parameter determination for Tikhonov regularization problems in general form
  J. Comput. Appl. Math., 343 (2018), pp. 12-25
  pdf file

• C. Fenu, L. Reichel, G. Rodriguez, and H. Sadok
  GCV for Tikhonov regularization by partial SVD
  BIT, 57 (2017), pp. 1019-1039
  pdf file

• A. Buccini, M. Donatelli, and L. Reichel
  Iterated Tikhonov regularization with a general penalty term
  Numer. Linear Algebra Appl., 24 (2017), e2089 (12 pages)
  pdf file

• L. Dykes, S. Noschese, and L. Reichel
  Circulant preconditioners for discrete ill-posed Toeplitz systems
  Numer. Algorithms, 75 (2017), pp. 477-490
  pdf file

• E. Onunwor and L. Reichel
  On the computation of a truncated SVD of a large linear discrete ill-posed problem
  Numer. Algorithms, 75 (2017), pp. 359-380
  pdf file

• S. Morigi, L. Reichel, and F. Sgallari
  Fractional Tikhonov regularization with a nonlinear penalty term
  J. Comput. Appl. Math., 324 (2017), pp. 142-154
  pdf file

• A. H. Bentbib, M. El Guide, K. Jbilou, and L. Reichel
  Global Golub-Kahan bidiagonalization applied to large discrete ill-posed problems
  J. Comput. Appl. Math., 322 (2017), pp. 46-56
  pdf file

• G. Huang, A. Lanza, S. Morigi, L. Reichel, and F. Sgallari
  Majorization-minimization generalized Krylov subspace methods for l_p-l_q optimization applied to image restoration
  BIT, 57 (2017), pp. 351-378
  pdf file

• Z.-Z. Bai, A. Buccini, K. Hayami, L. Reichel, J.-F. Yin, and N. Zheng
  Modulus-based iterative method for constrained Tikhonov regularization
  J. Comput. Appl. Math., 319 (2017), pp. 1-13
  pdf file

• C. Fenu, L. Reichel, and G. Rodriguez
  GCV for Tikhonov regularization via global Golub-Kahan decomposition
  Numer. Linear Algebra Appl., 23 (2016), pp. 467-484
  pdf file

• S. Gazzola and L. Reichel
  A new framework for multi-parameter regularization
  BIT, 56 (2016), pp. 919-949
  pdf file

• G. Huang, L. Reichel, and F. Yin
  On the choice of solution subspace for nonstationary iterated Tikhonov regularization
  Numer. Algorithms, 72 (2016), pp. 1043-1063
  pdf file

• G. Huang, L. Reichel, and F. Yin
  Projected nonstationary iterated Tikhonov regularization
  BIT, 56 (2016), pp. 467-487
  pdf file

• S. Noschese and L. Reichel
  Some matrix nearness problems suggested by Tikhonov regularization
  Linear Algebra Appl., 502 (2016), pp. 366-386
  pdf file

• G. Huang, S. Noschese, and L. Reichel
  Regularization matrices via matrix nearness problems
  Linear Algebra Appl., 502 (2016), pp. 41-57
  pdf file

• T. Mach, L. Reichel, M. Van Barel, and R. Vandebril
  Adaptive cross approximation for ill-posed problems
  J. Comput. Appl. Math., 303 (2016), pp. 206-217
  pdf file

• A. H. Bentbib, M. El Guide, K. Jbilou, and L. Reichel
  A global Lanczos method for image restoration
  J. Comput. Appl. Math., 300 (2016), pp. 233-244
  pdf file

• S. Gazzola, E. Onunwor, L. Reichel, and G. Rodriguez
  On the Lanczos and Golub-Kahan reduction methods applied to discrete ill-posed problems
  Numer. Linear Algebra Appl., 23 (2016), pp. 187-204
  pdf file

• D. Gerth, E. Klann, R. Ramlau, and L. Reichel
  On fractional Tikhonov regularization
  J. Inverse Ill-Posed Probl., 23 (2015), pp. 611-625
  pdf file

• L. Reichel and X. Yu
  Tikhonov regularization via flexible Arnoldi reduction
  BIT, 55 (2015), pp. 1145-1168
  pdf file

• A. Lanza, S. Morigi, L. Reichel, and F. Sgallari
  A generalized Krylov subspace method for l_p-l_q minimization
  SIAM J. Sci. Comput., 37 (2015), pp. S30-S50
  pdf file

• M. E. Hochstenbach, L. Reichel, and X. Yu
  A Golub-Kahan-type reduction method for matrix pairs
  J. Sci. Comput., 65 (2015), pp. 767-789
  pdf file

• M. E. Hochstenbach, S. Noschese, and L. Reichel
  Fractional regularization matrices for linear discrete ill-posed problems
  J. Eng. Math., 93 (2015), pp. 113-129
  pdf file

• A. Bouhamidi, K. Jbilou, L. Reichel, H. Sadok, and Z. Wang
  Vector extrapolation applied to truncated singular value decomposition and truncated iteration
  J. Eng. Math., 93 (2015), pp. 99-112
  pdf file

• L. Reichel and X. Yu
  Matrix decompositions for Tikhonov regularization
  Electron. Trans. Numer. Anal., 43 (2015), pp. 223-243
  pdf file

• T. A. Hearn and L. Reichel
  Image denoising via residual kurtosis minimization
  Numer. Math. Theor. Meth. Appl., 8 (2015), pp. 403-422
  pdf file

• M. Bellalij, L. Reichel, and H. Sadok
  Some properties of range restricted GMRES methods
  J. Comput. Appl. Math., 290 (2015), pp. 310-318
  pdf file

• S. Noschese and L. Reichel
  Lavrentiev-type regularization methods for Hermitian problems
  Calcolo, 52 (2015), pp. 187-205
  pdf file

• M. Donatelli, D. Martin, and L. Reichel
  Arnoldi methods for image deblurring with anti-reflective boundary conditions
  Appl. Math. Comput., 253 (2015), pp. 135-150
  pdf file

• L. Dykes, S. Noschese, and L. Reichel
  Rescaling the GSVD with application to ill-posed problems
  Numer. Algorithms, 68 (2015), pp. 531-545
  pdf file

• M. E. Hochstenbach, L. Reichel, and G. Rodriguez
  Regularization parameter determination for discrete ill-posed problems
  J. Comput. Appl. Math., 273 (2015), pp. 132-149
  pdf file

• S. Noschese and L. Reichel
  A modified TSVD method for discrete ill-posed problems
  Numer. Linear Algebra Appl., 21 (2014), pp. 813-822
  pdf file

• S. Noschese and L. Reichel
  Inverse subspace problems with applications
  Numer. Linear Algebra Appl., 21 (2014), pp. 589-603
  pdf file

• S. Morigi, L. Reichel, and F. Sgallari
  A general framework for nonlinear regularized Krylov-based image restoration
  in CompIMAGE 2014, eds. Y. Zhang and J. M. R. S. Tavares, Lecture Notes in Computer Science, vol. 8641, Springer, Berlin, 2014, pp. 273-279
  pdf file

• T. A. Hearn and L. Reichel
  Application of denoising methods to regularization of ill-posed problems
  Numer. Algorithms, 66 (2014), pp. 761-777
  pdf file

• M. Donatelli and L. Reichel
  Square smoothing regularization matrices with accurate boundary conditions
  J. Comput. Appl. Math., 272 (2014), pp. 334-349
  pdf file

• L. Dykes, F. Marcellan, and L. Reichel
  The structure of iterative methods for symmetric linear discrete ill-posed problems
  BIT, 54 (2014), pp. 129-145
  pdf file

• T. A. Hearn and L. Reichel
  Fast computation of convolution operations via low-rank approximation
  Appl. Numer. Math., 75 (2014), pp. 136-153
  pdf file

• K. Morikuni, L. Reichel, and K. Hayami
  FGMRES for linear discrete ill-posed problems
  Appl. Numer. Math., 75 (2014), pp. 175-187
  pdf file

• T. A. Hearn and L. Reichel
  Extensions of the Justen-Ramlau blind deconvolution method
  Adv. Comput. Math., 39 (2013), pp. 465-491
  pdf file

• D. R. Martin and L. Reichel
  Projected Tikhonov regularization of large-scale discrete ill-posed problems
  J. Sci. Comput., 56 (2013), pp. 471-493
  pdf file

• L. Dykes and L. Reichel
  A family of range restricted iterative methods for linear discrete ill-posed problems
  Dolomites Research Notes on Approximation, 6 (2013), pp. 27-36
  postscript file pdf file

• S. Morigi, L. Reichel, and F. Sgallari
  A cascadic alternating Krylov subspace image restoration method
  in Scale Space and Variational Methods in Computer Vision 2013, eds. A. Kuijper et al., Lecture Notes in Computer Science, vol 7893, Springer, Berlin, 2013, pp. 98-108
  pdf file

• L. Dykes and L. Reichel
  Simplified GSVD computations for the solution of linear discrete ill-posed problems
  J. Comput. Appl. Math., 255 (2013), pp. 15-27
  postscript file pdf file

• L. Reichel and G. Rodriguez
  Old and new parameter choice rules for discrete ill-posed problems
  Numer. Algorithms, 63 (2013), pp. 65-87
  postscript file pdf file

• D. R. Martin and L. Reichel
  Minimization of functionals on the solution of a large-scale discrete ill-posed problem
  BIT, 53 (2013), pp. 153-173
  pdf file

• M. K. Khan, S. Morigi, L. Reichel, and F. Sgallari
  Iterative methods of Richardson-Lucy-type for image deblurring
  Numer. Math. Theor. Meth. Appl., 6 (2013), pp. 262-275
  postscript file pdf file

• M. Donatelli, A. Neuman, and L. Reichel
  Square regularization matrices for large linear discrete ill-posed problems
  Numer. Linear Algebra Appl., 19 (2012), pp. 896-913
  postscript file pdf file

• L. Dykes and L. Reichel
  On the reduction of Tikhonov minimization problems and the construction of regularization matrices
  Numer. Algorithms, 60 (2012), pp. 683-696
  postscript file pdf file

• S. Noschese and L. Reichel
  Inverse problems for regularization matrices
  Numer. Algorithms, 60 (2012), pp. 531-544
  postscript file pdf file

• L. Reichel, F. Sgallari, and Q. Ye
  Tikhonov regularization based on generalized Krylov subspace methods
  Appl. Numer. Math., 62 (2012), pp. 1215-1228
  postscript file pdf file

• A. Neuman, L. Reichel, and H. Sadok
  Implementations of range restricted iterative methods for linear discrete ill-posed problems
  Linear Algebra Appl., 436 (2012), pp. 3974-3990
  postscript file pdf file

• M. E. Hochstenbach, N. McNinch, and L. Reichel
  Discrete ill-posed least-squares problems with a solution norm constraint
  Linear Algebra Appl., 436 (2012), pp. 3801-3818
  postscript file pdf file

• J. Lampe, L. Reichel, and H. Voss
  Large-scale Tikhonov regularization via reduction by orthogonal projection
  Linear Algebra Appl., 436 (2012), pp. 2845-2865
  postscript file pdf file

• M. Fuhry and L. Reichel
  A new Tikhonov regularization method
  Numer. Algorithms, 59 (2012), pp. 433-445
  pdf file

• J. O. Abad, S. Morigi, L. Reichel, and F. Sgallari
  Alternating Krylov subspace image restoration methods
  J. Comput. Appl. Math., 236 (2012), pp. 2049-2062
  postscript file pdf file

• A. Bouhamidi, K. Jbilou, L. Reichel, and H. Sadok
  A generalized global Arnoldi method for ill-posed matrix equations
  J. Comput. Appl. Math., 236 (2012), pp. 2078-2089
  postscript file pdf file

• M. E. Hochstenbach and L. Reichel
  Combining approximate solutions for linear discrete ill-posed problems
  J. Comput. Appl. Math., 236 (2012), pp. 2179-2185
  pdf file

• E. Klann, R. Ramlau, and L. Reichel
  Wavelet-based multilevel methods for linear ill-posed problems
  BIT, 51 (2011), pp. 669-694
  pdf file

• M. E. Hochstenbach and L. Reichel
  Fractional Tikhonov regularization for linear discrete ill-posed problems
  BIT, 51 (2011), pp. 197-215
  postscript file pdf file

• A. Bouhamidi, K. Jbilou, L. Reichel, and H. Sadok
  An extrapolated TSVD method for linear discrete ill-posed problems with Kronecker structure
  Linear Algebra Appl., 434 (2011), pp. 1677-1688
  pdf file

• S. Morigi, R. Plemmons, L. Reichel, and F. Sgallari
  A hybrid multilevel-active set method for large box-constrained linear discrete ill-posed problems
  Calcolo, 48 (2011), pp. 89-105
  postscript file pdf file

• M. E. Hochstenbach and L. Reichel
  An iterative method for Tikhonov regularization with a general linear regularization operator
  J. Integral Equations Appl., 22 (2010), pp. 463-480
  postscript file pdf file

• M. E. Hochstenbach and L. Reichel
  Subspace-restricted singular value decompositions for linear discrete ill-posed problems
  J. Comput. Appl. Math., 235 (2010), pp. 1053-1064
  postscript file pdf file

• S. Morigi, L. Reichel, and F. Sgallari
  Cascadic multilevel methods for fast nonsymmetric blur- and noise-removal
  Appl. Numer. Math., 60 (2010), pp. 378-396
  postscript file pdf file

• S. Morigi, L. Reichel, and F. Sgallari
  Noise-reducing cascadic multilevel methods for linear discrete ill-posed problems
  Numer. Algorithms, 53 (2010), pp. 1-22
  postscript file pdf file

• L. Reichel and A. Shyshkov
  Cascadic multilevel methods for ill-posed problems
  J. Comput. Appl. Math., 233 (2010), pp. 1314-1325
  postscript file pdf file

• S. Morigi, L. Reichel, and F. Sgallari
  An interior-point method for large constrained discrete ill-posed problems
  J. Comput. Appl. Math., 233 (2010), pp. 1288-1297
  postscript file pdf file

• S. Morigi, L. Reichel, and F. Sgallari
  An edge-preserving multilevel method for deblurring, denoising, and segmentation
  in Scale Space and Variational Methods in Computer Vision, eds. X.-C. Tai, K. Morken, M. Lysaker, and K.-A. Lie, Lecture Notes in Computer Science, vol. 5567, Springer, Berlin, 2009, pp. 427-438
  postscript file pdf file

• L. Reichel and Q. Ye
  Simple square smoothing regularization operators
  Electron. Trans. Numer. Anal., 33 (2009), pp. 63-83
  postscript file pdf file

• L. Reichel, G. Rodriguez, and S. Seatzu
  Error estimates for large-scale ill-posed problems
  Numer. Algorithms, 51 (2009), pp. 341-361
  postscript file pdf file

• K. Jbilou, L. Reichel, and H. Sadok
  Vector extrapolation enhanced TSVD for linear discrete ill-posed problems
  Numer. Algorithms, 51 (2009), pp. 195-208.
  postscript file pdf file

• B. Lewis and L. Reichel
  Arnoldi-Tikhonov regularization methods
  J. Comput. Appl. Math., 226 (2009), pp. 92-102
  postscript file pdf file

• L. Reichel and A. Shyshkov
  A new zero-finder for Tikhonov regularization
  BIT, 48 (2008), pp. 627-643
  postscript file pdf file

• L. Reichel and H. Sadok
  A new L-curve for ill-posed problems
  J. Comput. Appl. Math., 219 (2008), pp. 493-508
  postscript file pdf file

• S. Morigi, L. Reichel, F. Sgallari, and A. Shyshkov
  Cascadic multiresolution methods for image deblurring
  SIAM J. Imaging Sci., 1 (2008), pp. 51-74
  pdf file

• L. Reichel, H. Sadok, and A. Shyshkov
  Greedy Tikhonov regularization for large linear ill-posed problems
  Int. J. Comput. Math., 84 (2007), pp. 1151-1166
  postscript file pdf file

• S. Morigi, L. Reichel, and F. Sgallari
  Orthogonal projection regularization operators
  Numer. Algorithms, 44 (2007), pp. 99-114
  postscript file pdf file

• S. Morigi, L. Reichel, F. Sgallari, and F. Zama
  An iterative method for linear discrete ill-posed problems with box constraints
  J. Comput. Appl. Math., 198 (2007), pp. 505-520
  postscript file pdf file

• J. Baglama and L. Reichel
  Decomposition methods for large linear discrete ill-posed problems
  J. Comput. Appl. Math., 198 (2007), pp. 332-342
  postscript file pdf file

• S. Morigi, L. Reichel, and F. Sgallari
  A truncated projected SVD method for linear discrete ill-posed problems
  Numer. Algorithms, 43 (2006), pp. 197-213
  postscript file pdf file

• S. Morigi, L. Reichel, and F. Sgallari
  An iterative Lavrentiev regularization method
  BIT, 46 (2006), pp. 589-606
  postscript file pdf file

• S. Morigi, L. Reichel, F. Sgallari, and F. Zama
  Iterative methods for ill-posed problems and semiconvergent sequences
  J. Comput. Appl. Math., 193 (2006), pp. 157-167
  postscript file pdf file

• D. Calvetti, L. Reichel, and A. Shuibi
  Invertible smoothing preconditioners for linear discrete ill-posed problems
  Appl. Numer. Math., 54 (2005), pp. 135-149
  postscript file pdf file

• D. Calvetti, L. Reichel, and A. Shuibi
  Tikhonov regularization of large symmetric problems
  Numer. Linear Algebra Appl., 12 (2005), pp. 127-139
  postscript file pdf file

• D. Calvetti, B. Lewis, L. Reichel, and F. Sgallari
  Tikhonov regularization with nonnegativity constraint
  Electron. Trans. Numer. Anal., 18 (2004), pp. 153-173
  postscript file pdf file

• D. Calvetti, G. Landi, L. Reichel, and F. Sgallari
  Nonnegativity and iterative methods for ill-posed problems
  Inverse Problems, 20 (2004), pp. 1747-1758
  postscript file pdf file

• D. Calvetti and L. Reichel
  Tikhonov regularization with a solution constraint
  SIAM J. Sci. Comput, 26 (2004), pp. 224-239
  postscript file pdf file

• D. Calvetti, L. Reichel, and A. Shuibi
  L-curve and curvature bounds for Tikhonov regularization
  Numer. Algorithms, 35 (2004), pp. 301-314
  postscript file pdf file

• B. Lewis and L. Reichel
  Parallel deconvolution methods for three dimensional image restoration
  in Advanced Signal Processing Algorithms, Architecture, and Implementations XIII, ed. F. T. Luk, Proceedings of the Society of Photo-Optical Instrumentation Engineers (SPIE), vol. 5205, The International Society for Optical Engineering, Bellingham, WA, 2003, pp. 291-296
  postscript file pdf file

• D. Calvetti and L. Reichel
  Tikhonov regularization of large linear problems
  BIT, 43 (2003), pp. 263-283
  postscript file pdf file

• D. Calvetti, L. Reichel, and A. Shuibi
  Enriched Krylov subspace methods for ill-posed problems
  Linear Algebra Appl., 362 (2003), pp. 257-273
  postscript file pdf file

• D. Calvetti and L. Reichel
  Lanczos-based exponential filtering for discrete ill-posed problems
  Numer. Algorithms, 29 (2002), pp. 45-65
  postscript file pdf file

• D. Calvetti, B. Lewis, and L. Reichel
  A hybrid GMRES and TV-norm based method for image restoration
  in Advanced Signal Processing Algorithms, Architecture, and Implementations XIII, ed. F. T. Luk, Proceedings of the Society of Photo-Optical Instrumentation Engineers (SPIE), vol. 4791, The International Society for Optical Engineering, Bellingham, WA, 2002, pp. 192-200
  postscript file pdf file

• D. Calvetti, B. Lewis, and L. Reichel
  On the regularizing properties of the GMRES method
  Numer. Math., 91 (2002), pp. 605-625
  postscript file pdf file

• D. Calvetti, B. Lewis, and L. Reichel
  GMRES, L-curves, and discrete ill-posed problems
  BIT, 42 (2002), pp. 44-65
  postscript file pdf file

• D. Calvetti, P. C. Hansen, and L. Reichel
  L-curve curvature bounds via Lanczos bidiagonalization
  Electron. Trans. Numer. Anal., 14 (2002), pp. 20-35
  postscript file pdf file

• D. Calvetti, B. Lewis, and L. Reichel
  Krylov subspace iterative methods for nonsymmetric discrete ill-posed problems in image restoration
  in Advanced Signal Processing Algorithms, Architectures, and Implementations XI, ed. F. T. Luk, Proceedings of the Society of Photo-Optical Instrumentation Engineers (SPIE), vol. 4474, The International Society for Optical Engineering, Bellingham, WA, 2001, pp. 224-233
  postscript file pdf file

• D. Calvetti, B. Lewis, and L. Reichel
  On the choice of subspace for iterative methods for linear discrete ill-posed problems
  Int. J. Appl. Math. Comput. Sci., 11 (2001), pp. 1069-1092
  postscript file pdf file

Large-Scale Eigenvalue and Singular Value Problems

• A. El-Hachimi, K. Jbilou, A. Ratnani, and L. Reichel
  A tensor bidiagonalization method for higher-order singular value decomposition with applications
  Numer. Linear Algebra Appl., 31 (2024), Art e2530
  pdf file

• A. El Hachimi, K. Jbilou, A. Ratnani, and L. Reichel
  Spectral computation with third-order tensors using the t-product
  Appl. Numer. Math., 193 (2023), pp. 1-23
  pdf file

• M. Alkilayh, L. Reichel, and Q. Ye
  A method for computing a few eigenpairs of large generalized eigenvalue problems
  Appl. Numer. Math., 183 (2023), pp. 108-117
  pdf file

• J. Baglama and L. Reichel
  An implicitly restarted block Lanczos bidiagonalization method using Leja shifts
  BIT, 53 (2013), pp. 285-310
  pdf file

• J. Baglama and L. Reichel
  Augmented implicitly restarted Lanczos bidiagonalization methods
  SIAM J. Sci. Comput., 27 (2005), pp. 19-42
  postscript file pdf file

• J. Baglama, D. Calvetti, and L. Reichel
  IRBL: An implicitly restarted block Lanczos method for large-scale Hermitian eigenproblems
  SIAM J. Sci. Comput., 24 (2003), pp. 1650-1677
  postscript file pdf file

Iterative Methods for Linear and Nonlinear Systems of Equations

• A. Buccini, P. Diaz de Alba, F. Pes, and L. Reichel
  An efficient implementation of the Gauss-Newton method via generalized Krylov subspaces
  J. Sci. Comput., 97 (2023), Art. 44
  pdf file

• J. Ku and L. Reichel
  A novel iterative method for discrete Helmholtz decomposition
  Appl. Numer. Math., 151 (2020), pp. 161-171
  pdf file

• J. Ku and L. Reichel
  Simple efficient solvers for certain ill-conditioned systems of linear equations, including H(div) problems
  J. Comput. Appl. Math., 343 (2018), pp. 240-249
  pdf file

• M. Alkilayh, L. Reichel, and J. Y. Yuan
  New zero-finders for trust-region computations
  Numer. Algorithms, 76 (2017), pp. 361-375
  pdf file

• S. Noschese and L. Reichel
  A note on superoptimal generalized circulant preconditioners
  Appl. Numer. Math., 75 (2014), pp. 188-195
  pdf file

• J. Baglama, L. Reichel, and D. Richmond
  An augmented LSQR method
  Numer. Algorithms, 64 (2013), pp. 263-293
  pdf file

• B. Philippe and L. Reichel
  On the generation of Krylov subspace bases
  Appl. Numer. Math., 62 (2012), pp. 1171-1186
  postscript file pdf file

• S. Noschese and L. Reichel
  Generalized circulant Strang-type preconditioners
  Numer. Linear Algebra Appl., 19 (2012), pp. 3-17
  postscript file pdf file

• L. Reichel and Q. Ye
  A generalized LSQR algorithm
  Numer. Linear Algebra Appl., 15 (2008), pp. 643-660
  postscript file pdf file

• B. Beckermann and L. Reichel
  The Arnoldi process and GMRES for nearly symmetric matrices
  SIAM J. Matrix Anal. Appl., 30 (2008), pp. 102-120
  pdf file

• J. Baglama and L. Reichel
  Augmented GMRES-type methods
  Numer. Linear Algebra Appl., 14 (2007), pp. 337-350
  pdf file

• L. Reichel and Q. Ye
  Breakdown-free GMRES for singular systems
  SIAM J. Matrix Anal. Appl., 26 (2005), pp. 1001-1021
  postscript file pdf file

• D. Calvetti and L. Reichel
  Gauss quadrature applied to trust region computations
  Numer. Algorithms, 34 (2003), pp. 85-102
  postscript file pdf file

• D. Calvetti and L. Reichel
  Pole placement preconditioning
  Linear Algebra Appl., 366 (2003), pp. 99-120
  postscript file pdf file

• D. Calvetti, S. Morigi, L. Reichel, and F. Sgallari
  An iterative method with error estimators
  J. Comput. Appl. Math., 127 (2001), pp. 93-119
  postscript file pdf file

Integral Equations

• L. Fermo, L. Reichel, G. Rodriguez, and M. M. Spalevic'
  Averaged Nystrom interpolants for the solution of Fredholm integral equations of the second kind
  Appl. Math. Comput., 467 (2024), Art. 128482
  pdf file

Structured Problems in Linear Algebra

• S. Noschese and L. Reichel
  On the banded Toeplitz structured distance to symmetric positive semidefiniteness
  Electron. J. Linear Algebra, 38 (2022), pp. 260-273
  pdf file

• M. Kuian, L. Reichel, and S. V. Shiyanovskii
  Optimally conditioned Vandermonde-like matrices
  SIAM J. Matrix Anal. Appl., 40 (2019), pp. 1399-1424
  pdf file

• M. Kuian, L. Reichel, and S. V. Shiyanovskii
  Fast factorization of rectangular Vandermonde matrices with Chebyshev nodes
  Numer. Algorithms, 81 (2019), pp. 547-559
  pdf file

• S. Noschese and L. Reichel
  Eigenvector sensitivity under general and structured perturbations of tridiagonal Toeplitz-type matrices
  Numer. Linear Algebra Appl., 26 (2019), e2232 (20 pages)
  pdf file

• S. Noschese and L. Reichel
  Computing unstructured and structured polynomial pseudospectrum approximations
  J. Comput. Appl. Math., 350 (2019), pp. 57-68
  pdf file

• M. Kuian, L. Reichel, and S. V. Shiyanovskii
  Accuracy optimization of combined multiparameter measuring systems with application to polarized light microscopy
  Phys. Rev. E, 97 (2018), 063305 (8 pages)
  pdf file

• S. Noschese and L. Reichel
  Approximated structured pseudospectra
  Numer. Linear Algebra Appl., 24 (2017), e2082 (11 pages)
  pdf file

• D. Calvetti, L. Reichel, and H. Xu
  A CS decomposition for orthogonal matrices with application to eigenvalue computation
  Linear Algebra Appl., 476 (2015), pp. 197-232
  pdf file

• C. Jagels and L. Reichel
  The structure of matrices in rational Gauss quadrature
  Math. Comp., 82 (2013), pp. 2035-2060
  postscript file pdf file

• S. Noschese, L. Pasquini, and L. Reichel
  Tridiagonal Toeplitz matrices: properties and novel applications
  Numer. Linear Algebra Appl., 20 (2013), pp. 302-326
  postscript file pdf file

• S. Noschese and L. Reichel
  The structured distance to normality of Toeplitz matrices with application to preconditioning
  Numer. Linear Algebra Appl., 18 (2011), pp. 429-447
  postscript file pdf file

• C. Jagels and L. Reichel
  Recursion relations for the extended Krylov subspace method
  Linear Algebra Appl., 434 (2011), pp. 1716-1732
  postscript file pdf file

• S. Noschese and L. Reichel
  The structured distance to normality of banded Toeplitz matrices
  BIT, 49 (2009), pp. 629-640
  postscript file pdf file

• C. Jagels and L. Reichel
  The extended Krylov subspace method and orthogonal Laurent polynomials
  Linear Algebra Appl., 431 (2009), pp. 441-458
  postscript file pdf file

• S. Noschese, L. Pasquini, and L. Reichel
  The structured distance to normality of an irreducible real tridiagonal matrix
  Electron. Trans. Numer. Anal., 28 (2007), pp. 65-77
  postscript file pdf file

• D. Calvetti, S.-M. Kim, and L. Reichel
  The restarted QR-algorithm for eigenvalue computation of structured matrices
  J. Comput. Appl. Math., 149 (2002), pp. 415-422
  postscript file pdf file

• D. Calvetti, B. Lewis, and L. Reichel
  Partial eigenvalue assignment for large linear control systems
  Structured Matrices in Mathematics, Computer Science and Engineering I, ed. V. Olshevsky, Contemporary Mathematics, vol. 280, Amer. Math. Soc., Providence, RI, 2001, pp. 241-254
  postscript file pdf file

• D. Calvetti, B. Lewis, and L. Reichel
  On the solution of large Sylvester-observer equations
  Numer. Linear Algebra Appl., 8 (2001), pp. 435-451
  postscript file pdf file

Network Analysis

• S. Noschese and L. Reichel
  Enhancing multiplex global efficiency
  Numer. Algorithms, 96 (2024), pp. 397-416
  pdf file

• S. El-Halouy, S. Noschese, and L. Reichel
  A tensor formalism for multilayer network centrality measures using the Einstein product
  Appl. Numer. Math., 200 (2024), pp. 236-253
  pdf file

• S. Noschese and L. Reichel
  Network analysis with the aid of the path length matrix
  Numer. Algorithms, 95 (2024), pp. 451-470
  pdf file

• S. El-Halouy, S. Noschese, and L. Reichel
  Perron communicability and sensitivity of multilayer networks
  Numer. Algorithms, 92 (2023), pp. 597-617
  pdf file

• S. Noschese and L. Reichel
  Estimating and increasing the structural robustness of a network
  Numer. Linear Algebra Appl., 29 (2022), e2418
  pdf file

• A. Concas, C. Fenu, L. Reichel, G. Rodriguez, and Y. Zhang
  Chained structure of directed graphs with applications to social and transportation networks
  Appl. Netw. Sci., 7 (2022), Art. 64
  pdf file

• O. De la Cruz Cabrera, J. Jin, S. Noschese, and L. Reichel
  Communication in complex networks
  Appl. Numer. Math., 172 (2022), pp. 186-205
  pdf file

• O. De la Cruz Cabrera, M. Matar, and L. Reichel
  Centrality measures for node-weighted networks via line graphs and the matrix exponential
  Numer. Algorithms, 88 (2021), pp. 583-614
  pdf file

• A. Concas, L. Reichel, G. Rodriguez, and Y. Zhang
  Iterative methods for the computation of the Perron vector of adjacency matrices
  Mathematics, 9 (2021), Art. 1522
  pdf file

• A. Concas, L. Reichel, G. Rodriguez, and Y. Zhang
  Chained graphs and some applications
  Appl. Netw. Sci., 6 (2021), Art. 39
  pdf file

• O. De la Cruz Cabrera, J. Jin, and L. Reichel
  New models for multi-class networks
  J. Comput. Appl. Math., 394 (2021), Art. 113567
  pdf file

• M. Al Mugahwi, O. De la Cruz Cabrera, C. Fenu, L. Reichel, and G. Rodriguez
  Block matrix models for dynamic networks
  Appl. Math. Comput., 402 (2021), Art. 126121
  pdf file

• M. Al Mugahwi, O. De la Cruz Cabrera, S. Noschese, and L. Reichel
  Functions and eigenvectors of partially known matrices with applications to network analysis
  Appl. Numer. Math., 159 (2021), pp. 93-105
  pdf file

• M. Al Mugahwi, O. De la Cruz Cabrera, and L. Reichel
  Orthogonal expansion of network functions
  Vietnam J. Math., 48 (2020), pp. 941-962
  pdf file

• A. Concas, S. Noschese, L. Reichel, and G. Rodriguez
  A spectral method for bipartizing a network and detecting a large anti-community
  J. Comput. Appl. Math., 373 (2020), Art. 112306
  pdf file

• O. De la Cruz Cabrera, M. Matar, and L. Reichel
  Edge importance in a network via line graphs and the matrix exponential
  Numer. Algorithms, 83 (2020), pp. 807-832
  pdf file

• O. De la Cruz Cabrera, M. Matar, and L. Reichel
  Analysis of directed networks via the matrix exponential
  J. Comput. Appl. Math., 355 (2019), pp. 182-192
  pdf file

• J. Baglama, C. Fenu, L. Reichel, and G. Rodriguez
  Analysis of directed networks via partial singular value decomposition and Gauss quadrature
  Linear Algebra Appl., 456 (2014), pp. 93-121
  pdf file

• C. Fenu, D. Martin, L. Reichel, and G. Rodriguez
  Network analysis via partial spectral factorization and Gauss quadrature
  SIAM J. Sci. Comput., 35 (2013), pp. A2046-A2068
  pdf file

Quadrature and Orthogonal Polynomials

• D. Lj. Djukic', R. M. Mutavdzic' Djukic', L. Reichel, and M. M. Spalevic'
  Weighted averaged Gaussian quadrature rules for modified Chebyshev measures
  Appl. Numer. Math., 200 (2024), pp. 195-208
  pdf file

• H. Almutairi, M. Pranic', and L. Reichel
  Error estimates for quadrature rules based on the Arnoldi process
  J. Comput. Appl. Math., 442 (2024), Art. 115726
  pdf file

• D. Lj. Djukic', R. M. Mutavdzic' Djukic', L. Reichel, and M. M. Spalevic'
  Decompositions of optimal averaged Gauss quadrature rules
  J. Comput. Appl. Math., 438 (2024), Art. 115586
  pdf file

• L. Reichel and M. M. Spalevic'
  Radau and Lobatto averaged Gaussian quadrature rules
  J. Comput. Appl. Math., 437 (2024), Art. 115475
  pdf file

• D. Lj. Djukic', R. M. Mutavdzic' Djukic', L. Reichel, and M. M. Spalevic'
  Internality of averaged Gauss quadrature rules for certain modification of Jacobi measures
  Appl. Comput. Math. (Baku), 22 (2023), pp. 426-442
  pdf file

• D. Lj. Djukic', R. M. Mutavdzic' Djukic', L. Reichel, and M. M. Spalevic'
  Internality of generalized averaged Gauss quadrature rules and truncated variants for modified Chebyshev measures of the third and fourth kinds
  Numer. Algorithms, 92 (2023), pp. 523-544
  pdf file

• A. Bentbib, M. El Ghomari, K. Jbilou, and L. Reichel
  The global Golub-Kahan method and Gauss quadrature for tensor function  approximation
  Numer. Algorithms, 92 (2023), pp. 5-34
  pdf file

• J. Alahmadi, M. Pranic', and L. Reichel
  Pole allocation for rational Gauss quadrature rules for matrix functionals defined by a Stieltjes function
  Axioms, 12 (2023), Art. 105
  pdf file

• J. Alahmadi, M. Pranic', and L. Reichel
  Rational Gauss quadrature rules for the approximation of matrix functionals involving Stieltjes functions
  Numer. Math., 151 (2022), pp. 443-473
  pdf file

• L. Reichel and M. M. Spalevic'
  Averaged Gauss quadrature formulas: Properties and applications
  J. Comput. Appl. Math., 410 (2022), Art. 114232
  pdf file

• A. Bentbib, M. El Ghomari, K. Jbilou, and L. Reichel
  The extended symmetric block Lanczos method for matrix-valued Gauss-type quadrature rules
  J. Comput. Appl. Math., 407 (2022), Art. 113965
  pdf file

• J. Alahmadi, H. Alqahtani, M. S. Pranic', and L. Reichel
  Gauss-Laurent-type quadrature rules for the approximation of functionals of a nonsymmetric matrix
  Numer. Algorithms, 88 (2021), pp. 1937-1964
  pdf file

• D. Lj. Djukic', R. M. Mutavdzic' Djukic', L. Reichel, and M. M. Spalevic'
  Internality of generalized averaged Gauss quadrature rules and truncated variants for modified Chebyshev measures of the first kind
  J. Comput. Appl. Math., 398 (2021), Art. 113696
  pdf file

• J. Alahmadi, M. S. Pranic', and L. Reichel
  Computation of error bounds via generalized Gauss-Radau and Gauss-Lobatto rules
  J. Comput. Appl. Math., 396 (2021), Art. 113604
  pdf file

• L. Reichel and M. M. Spalevic'
  A new representation of generalized averaged Gauss quadrature rules
  Appl. Numer. Math., 165 (2021), pp. 614-619
  pdf file

• A. H. Bentbib, M. El Ghomari, K. Jbilou, and L. Reichel
  Shifted extended global Lanczos processes for trace estimation with application to network analysis
  Calcolo, 58 (2021), Art. 4
  pdf file

• N. Eshghi, T. Mach, and L. Reichel
  New matrix function approximations and quadrature rules based on the Arnoldi process
  J. Comput. Appl. Math., 391 (2021), Art. 113442
  pdf file

• C. Jagels, K. Jbilou, and L. Reichel
  The extended global Lanczos method, Gauss-Radau quadrature, and matrix function approximation
  J. Comput. Appl. Math., 381 (2021), Art. 113027
  pdf file

• L. Reichel, M. M. Spalevic', and J. D. Tomanovic'
  Rational averaged Gauss quadrature rules
  FILOMAT, 34:2 (2020), pp. 379-389
  pdf file

• H. Alqahtani and L. Reichel
  Generalized block anti-Gauss quadrature rules
  Numer. Math., 143 (2019), pp. 605-648
  pdf file

• D. Lj. Djukic', L. Reichel, and M. M. Spalevic'
  Internality of generalized averaged Gaussian quadrature rules and truncated variants for measures induced by Chebyshev polynomials
  Appl. Numer. Math., 142 (2019), pp. 190-205
  pdf file

• D. Lj. Djukic', L. Reichel, M. M. Spalevic', and J. D. Tomanovic'
  Internality of generalized averaged Gaussian quadrature rules and truncated variants for modified Chebyshev measures of the second kind
  J. Comput. Appl. Math., 345 (2019), pp. 70-85
  pdf file

• A. H. Bentbib, M. El Ghomari, C. Jagels, K. Jbilou, and L. Reichel
  The extended global Lanczos method for matrix function approximation
  Electron. Trans. Numer. Anal., 50 (2018), pp. 144-163
  pdf file

• H. Alqahtani and L. Reichel
  Multiple orthogonal polynomials applied to matrix function evaluation
  BIT, 58 (2018), pp. 835-859
  pdf file

• H. Alqahtani and L. Reichel
  Simplified anti-Gauss quadrature rules with applications in linear algebra
  Numer. Algorithms, 77 (2018), pp. 577-602
  pdf file

• N. Eshghi, L. Reichel, and M. M. Spalevic
  Enhanced matrix function approximation
  Electron. Trans. Numer. Anal., 47 (2017), pp. 197-205
  pdf file

• C. Jagels, L. Reichel, and T. Tang
  Generalized averaged Szego quadrature rules
  J. Comput. Appl. Math., 311 (2017), pp. 645-654
  pdf file

• D. Lj. Djukic', L. Reichel, M. M. Spalevic', and J. D. Tomanovic'
  Internality of generalized averaged Gauss rules and their truncations for Bernstein-Szego weights
  Electron. Trans. Numer. Anal., 45 (2016), pp. 405-419
  pdf file

• D. Lj. Djukic', L. Reichel, and M. M. Spalevic'
  Truncated generalized averaged Gauss quadrature rules
  J. Comput. Appl. Math., 308 (2016), pp. 408-418
  pdf file

• L. Reichel, G. Rodriguez, and T. Tang
  New block quadrature rules for the approximation of matrix functions
  Linear Algebra Appl., 502 (2016), pp. 299-326
  pdf file

• L. Reichel, M. M. Spalevic', and T. Tang
  Generalized averaged Gauss quadrature rules for the approximation of matrix functionals
  BIT, 56 (2016), pp. 1045-1067
  pdf file

• C. Jagels and L. Reichel
  On the computation of Gauss quadrature rules for measures with a monomial denominator
  J. Comput. Appl. Math., 286 (2015), pp. 102-113
  pdf file

• M. S. Pranic' and L. Reichel
  Generalized anti-Gauss quadrature rules
  J. Comput. Appl. Math., 284 (2015), pp. 235-243
  pdf file

• M. Bellalij, L. Reichel, G. Rodriguez, and H. Sadok
  Bounding matrix functionals via partial global block Lanczos decomposition
  Appl. Numer. Math., 94 (2015), pp. 127-139
  pdf file

• M. S. Pranic' and L. Reichel
  Rational Gauss quadrature
  SIAM J. Numer. Anal., 52 (2014), pp. 832-851
  pdf file

• L. Reichel
  Polynomials orthogonal on the semicircle
  in Walter Gautschi: Selected Works with Commentaries, vol. 2, eds. C. Brezinski and A. Sameh, Springer, New York, 2014, pp. 17-22
  pdf file

• C. Fenu, D. Martin, L. Reichel, and G. Rodriguez
  Block Gauss and anti-Gauss quadrature with application to networks
  SIAM J. Matrix Anal. Appl., 34 (2013), pp. 1655-1684
  pdf file

• S.-M. Kim and L. Reichel
  Sensitivity analysis for Szego polynomials
  Numer. Math., 113 (2009), pp. 265-279
  postscript file pdf file

• B. de la Calle Ysern, G. Lo'pez Lagomasino, and L. Reichel
  Stieltjes-type polynomials on the unit circle
  Math. Comp., 78 (2009), pp. 969-997
  postscript file pdf file

• G. Lo'pez Lagomasino, L. Reichel, and L. Wunderlich
  Matrices, moments, and rational quadrature
  Linear Algebra Appl., 429 (2008), pp. 2540-2554
  postscript file pdf file

• S.-M. Kim and L. Reichel
  Anti-Szego quadrature rules
  Math. Comp., 76 (2007), pp. 795-810
  postscript file pdf file

• C. Jagels and L. Reichel
  Szego-Lobatto quadrature rules
  J. Comput. Appl. Math., 200 (2007), pp. 116-126
  postscript file pdf file

• D. Calvetti, S.-M. Kim, and L. Reichel
  Quadrature rules based on the Arnoldi process
  SIAM J. Matrix Anal., 26 (2005), pp. 765-781
  postscript file pdf file

• D. Calvetti and L. Reichel
  Symmetric Gauss-Lobatto and modified anti-Gauss rules
  BIT, 43 (2003), pp. 541-554
  postscript file pdf file

Polynomial Computation, Rational Approximation, and Matrix Functions

• D. Lj. Djukic', R. M. Mutavdzic' Djukic', L. Reichel, and M. M. Spalevic'
  Optimal averaged Pade'-type approximants
  Electron. Trans. Numer. Math., 59 (2023), pp. 145-156
  pdf file

• N. Eshghi and L. Reichel
  Estimating the error in matrix function approximations
  Adv. Comput. Math., 47 (2021), Art. 57
  pdf file

• M. Pranic', L. Reichel, G. Rodriguez, Z. Wang, and X. Yu
  A rational Arnoldi process with applications
  Numer. Linear Algebra Appl., 23 (2016), pp. 1007-1022
  pdf file

• C. Jagels, T. Mach, L. Reichel, and R. Vandebril
  Convergence rates for inverse-free rational approximation of matrix functions
  Linear Algebra Appl., 510 (2016), pp. 291-310
  pdf file

• M. S. Pranic' and L. Reichel
  Recurrence relations for orthogonal rational functions
  Numer. Math., 123 (2013), pp. 629-642
  postscript file pdf file

• B. Beckermann and L. Reichel
  Error estimation and evaluation of matrix functions via the Faber transform
  SIAM J. Numer. Anal., 47 (2009), pp. 3849-3883
  pdf file

• D. Calvetti and L. Reichel
  On the evaluation of polynomial coefficients
  Numer. Algorithms, 33 (2003), pp. 153-161
  postscript file pdf file

• D. Calvetti, L. Reichel, and F. Sgallari
  A modified companion matrix method based on Newton polynomials
  Fast Algorithms for Structured Matrices: Theory and Applications, ed. V. Olshevsky, Contemporary Mathematics, vol. 323, Amer. Math. Soc., Providence, RI, 2003, pp. 179-186
  postscript file pdf file

• G. S. Ammar, D. Calvetti, W. B. Gragg, and L. Reichel
  Polynomial zerofinders based on Szego polynomials
  J. Comput. Appl. Math., 127 (2001), pp. 1-16
  postscript file pdf file

Bioinformatics

• Z.-H. Duan, B. Hughes, L. Reichel, D. M. Perez, and T. Shi
  The relationship between protein sequences and their gene ontology functions
  BMC Bioinformatics, 7 (Suppl 4) (2006), S11 (11 pages)
  html file

Software

• A. Buccini, L. Onisk, and L. Reichel
  Range restricted iterative methods for linear discrete ill-posed problems
  Electron. Trans. Numer. Anal., 58 (2023), pp. 348-377
  pdf file

• A. Alqahtani, T. Mach, and L. Reichel
  Solution of ill-posed problems with Chebfun
  Numer. Algorithms, 92 (2023), pp. 2341-2364
  pdf file

• C. Fenu, L. Reichel, and G. Rodriguez
  SoftNet: A package for the analysis of complex networks
  Algorithms, 15 (2022), Art. 296
  pdf file

• J. Baglama, L. Reichel, and B. W. Lewis
  irlba: Fast truncated SVD, PCA and symmetric eigendecomposition for large dense and sparse matrices
  R package version 2.1.2, 2016. Available at https://CRAN.R-project.org/package=irlba
  This is a package for the statistical computing environment R. It is the leading algorithm for truncated SVD computations. The algorithm has been downloaded more than one million times.

• A. Neuman, L. Reichel, and H. Sadok
  Algorithms for range restricted iterative methods for linear discrete ill-posed problems
  Numer. Algorithms, 59 (2012), pp. 325-331
  postscript file pdf file

• J. Baglama and L. Reichel
  Restarted block Lanczos bidiagonalization methods
  Numer. Algorithms, 43 (2006), pp. 251-272
  postscript file pdf file

• J. Baglama, D. Calvetti, and L. Reichel
  Algorithm 827: irbleigs: A MATLAB program for computing a few eigenpairs of a large sparse Hermitian matrix
  ACM Trans. Math. Software, 29 (2003), pp. 337-348
  postscript file pdf file