Publications

Recent technical reports

[1]
A. Cortinovis, D. Kressner, S. Massei, and B. Peherstorfer. Quasi-optimal sampling to learn basis updates for online adaptive model reduction with adaptive empirical interpolation. Technical report, September 2019. (PDF, 327 kB)

[2]
S. Massei, L. Robol, and D. Kressner. hm-toolbox: Matlab software for HODLR and HSS matrices. Technical report, September 2019. (PDF, 505 kB)

[3]
A. Cortinovis and D. Kressner. Low-rank approximation in the Frobenius norm by column and row subset selection. Technical report, August 2019. (PDF, 502 kB)

[4]
S. Massei and L. Robol. Rational Krylov for Stieltjes matrix functions: Convergence and pole selection. Technical report, August 2019. (PDF, 535 kB)

[5]
M. Chen and D. Kressner. Recursive blocked algorithms for linear systems with Kronecker product structure. Technical report, May 2019. (PDF, 383 kB)

[6]
F. Statti. Polynomial bounds for European option pricing. Technical report, March 2019. (PDF, 675 kB)

[7]
D. Kressner, P. Kürschner, and S. Massei. Low-rank updates and divide-and-conquer methods for quadratic matrix equations. Technical report, March 2019. (PDF, 436 kB)

[8]
K. Glau, D. Kressner, and F. Statti. Low-rank tensor approximation for Chebyshev interpolation in parametric option pricing. Technical report, February 2019. (PDF, 965 kB)

[9]
A. Cortinovis, D. Kressner, and S. Massei. On maximum volume submatrices and cross approximation for symmetric semidefinite and diagonally dominant matrices. Technical report, February 2019. (PDF, 325 kB)

[10]
S. Hautphenne and S. Massei. A low-rank technique for computing the quasi-stationary distribution of subcritical Galton-Watson processes. Technical report, January 2019. (PDF, 1286 kB)

[11]
D. Kressner and A. Šušnjara. Fast QR decomposition of HODLR matrices. Technical report, September 2018. (PDF, 453 kB)

[12]
S. Massei, M. Mazza, and L. Robol. Fast solvers for 2D fractional diffusion equations using rank structured matrices. Technical report, April 2018. (PDF, 572 kB)

[13]
A. Šušnjara and D. Kressner. A fast spectral divide-and-conquer method for banded matrices. Technical report, January 2018. (PDF, 513 kB)

[14]
D. Kressner, S. Massei, and L. Robol. Low-rank updates and a divide-and-conquer method for linear matrix equations. Technical report, December 2017. (PDF, 522 kB)

[15]
A. Frommer, C. Schimmel, and M. Schweitzer. Bounds for the decay of the entries in inverses and Cauchy–Stieltjes functions of sparse, normal matrices. Technical report, April 2017. (PDF, 503 kB)

[16]
R. Luce and O. Sète. The index of singular zeros of harmonic mappings of anti-analytic degree one. Technical report, January 2017. (PDF, 1999 kB)

Books

[1]
A. Abdulle, S. Deparis, D. Kressner, F. Nobile, and M. Picasso (Eds.). Numerical Mathematics and Advanced Applications - ENUMATH 2013. Proceedings of ENUMATH 2013, the 10th European Conference on Numerical Mathematics and Advanced Applications, Lausanne, August 2013. Springer. Lecture Notes in Computational Science and Engineering, vol. 103. 2015.

[2]
P. Benner, M. Bollhöfer, D. Kressner, C. Mehl, and T. Stykel (Eds.). Numerical Algebra, Matrix Theory, Differential-Algebraic Equations and Control Theory. Festschrift in Honor of Volker Mehrmann. Springer. 2015.

[3]
D. Kressner. Numerical Methods for General and Structured Eigenvalue Problems. Springer, Heidelberg. Lecture Notes in Computational Science and Engineering, vol. 46. 2005. (PDF, 1631 kB)

Refereed articles in journals

The versions of the papers that can be downloaded from this page represent preliminary versions of the papers and not the final version published. You are advised to prefer the published articles as they contain the most recent versions.
[1]
D. A. Bini, S. Massei, and L. Robol. Quasi-Toeplitz matrix arithmetic: a MATLAB toolbox. Numerical Algorithms, 2018. (PDF, 503 kB)

[2]
S. Massei, D. Palitta, and L. Robol. Solving rank-structured Sylvester and Lyapunov equations. SIAM Journal on Matrix Analysis and Applications, 39(4):1564–1590, 2018. (PDF, 695 kB)

[3]
D. Kressner. A Krylov subspace method for the approximation of bivariate matrix functions. Technical report, February 2018. Revised July 2018. To appear. (PDF, 234 kB)

[4]
Z. Bujanović, L. Karlsson, and D. Kressner. A Householder-based algorithm for Hessenberg-triangular reduction. SIAM J. Matrix Anal. Appl., 39(3):1270–1294, 2018. (PDF, 595 kB)

[5]
B. Beckermann, D. Kressner, and M. Schweitzer. Low-rank updates of matrix functions. SIAM J. Matrix Anal. Appl., 39(1):539–565, 2018. (PDF, 566 kB)

[6]
P. Sirkovic. A reduced basis approach to large-scale pseudospectra computation. Technical report, September 2016. Revised 2018. To appear. (PDF, 2237 kB)

[7]
D. Filipović, M. Larsson, and F. Statti. Unspanned Stochastic Volatility in the Multi-Factor CIR Model. Mathematical Finance, May 2017. To appear. (PDF, 367 kB)

[8]
D. Kressner, D. Lu, and B. Vandereycken. Subspace acceleration for the Crawford number and related eigenvalue optimization problems. SIAM J. Matrix Anal. Appl., 39(2):961–982, 2018. (PDF, 728 kB)

[9]
D. Kressner and R. Luce. Fast computation of the matrix exponential for a Toeplitz matrix. SIAM J. Matrix Anal. Appl., 39(1):23–47, 2018. (PDF, 604 kB)

[10]
D. Kressner and L. Periša. Recompression of Hadamard products of tensors in Tucker format. SIAM J. Sci. Comput., 39(5):A1879–A1902, 2017. (PDF, 485 kB)

[11]
M. Bolten, K. Kahl, D. Kressner, F. Macedo, and S. Sokolović. Multigrid methods combined with low-rank approximation for tensor structured Markov chains. Technical report, April 2016. To appear. (PDF, 439 kB)

[12]
N. Gillis and R. Luce. A Fast Gradient Method for Nonnegative Sparse Regression With Self-Dictionary. IEEE Transactions on Image Processing, 27(1):24–37, 2018. (PDF, 1504 kB)

[13]
D. Kressner, R. Luce, and F. Statti. Incremental computation of block triangular matrix exponentials with application to option pricing. Electron. Trans. Numer. Anal., 47:57–72, 2017. (PDF, 367 kB)

[14]
D. Thanou, X. Dong, D. Kressner, and P. Frossard. Learning heat diffusion graphs. IEEE Trans. Signal Inform. Process. Netw., 3(3):484–499, 2017. (PDF, 4870 kB)

[15]
D. Kressner and A. Šušnjara. Fast computation of spectral projectors of banded matrices. SIAM J. Matrix Anal. Appl., 38(3):984–1009, 2017. (PDF, 654 kB)

[16]
W. Hackbusch, D. Kressner, and A. Uschmajew. Perturbation of higher-order singular values. SIAM J. Appl. Algebra Geometry, 2017. To appear. (PDF, 196 kB)

[17]
J. Ballani, D. Kressner, and M. D. Peters. Multilevel tensor approximation of PDEs with random data. Stoch. Partial Differ. Equ. Anal. Comput., 5(3):400–427, 2017. (PDF, 411 kB)

[18]
N. Guglielmi, M.-U. Rehman, and D. Kressner. A novel iterative method to approximate structured singular values. SIAM J. Matrix Anal. Appl., 38(2):361–386, 2017. (PDF, 455 kB)

[19]
E. Begović Kovač and D. Kressner. Structure-preserving low multilinear rank approximation of antisymmetric tensors. SIAM J. Matrix Anal. Appl., 38(3):967–983, 2017. (PDF, 399 kB)

[20]
M. Steinlechner. Riemannian Optimization for High-Dimensional Tensor Completion. SIAM J. Sci. Comput., 38(5):S461–S484, 2016. (PDF, 399 kB)

[21]
F. Bonizzoni, F. Nobile, and D. Kressner. Tensor train approximation of moment equations for elliptic equations with lognormal coefficient. Comput. Methods Appl. Mech. Engrg., 308:349–376, 2016. (PDF, 771 kB)

[22]
D. Kressner, M. Steinlechner, and B. Vandereycken. Preconditioned low-rank Riemannian optimization for linear systems with tensor product structure. SIAM J. Sci. Comput., 38(4):A2018–A2044, 2016. (PDF, 607 kB)

[23]
J. Ballani and D. Kressner. Reduced basis methods: from low-rank matrices to low-rank tensors. SIAM J. Sci. Comput., 38(4):A2045–A2067, 2016. (PDF, 362 kB)

[24]
P. Sirković and D. Kressner. Subspace acceleration for large-scale parameter-dependent Hermitian eigenproblems. SIAM J. Matrix Anal. Appl., 37(2):695–718, 2016. (PDF, 499 kB)

[25]
R. Luce, P. Hildebrandt, U. Kuhlmann, and J. Liesen. Using Separable Nonnegative Matrix Factorization Techniques for the Analysis of Time-Resolved Raman Spectra. Applied Spectroscopy, 70(9):1464–1475, September 2016.

[26]
J. Liesen and R. Luce. Fast recovery and approximation of hidden Cauchy structure. Linear Algebra Appl., 493:261–280, 2016. (PDF, 536 kB)

[27]
F. M. Dopico, J. González, D. Kressner, and V. Simoncini. Projection methods for large-scale T-Sylvester equations. Math. Comp., 85(301):2427–2455, 2016. (PDF, 599 kB)

[28]
D. Kressner and A. Uschmajew. On low-rank approximability of solutions to high-dimensional operator equations and eigenvalue problems. Linear Algebra Appl., 493:556–572, 2016. (PDF, 175 kB)

[29]
L. Karlsson, D. Kressner, and A. Uschmajew. Parallel algorithms for tensor completion in the CP format. Parallel Comput., 57:222–234, 2016. (PDF, 440 kB)

[30]
A. Uschmajew. A new convergence proof for the higher-order power method and generalizations. Pac. J. Optim., 11(2):309–321, 2015. (PDF, 275 kB)

[31]
J. Ballani and L. Grasedyck. Hierarchical tensor approximation of output quantities of parameter-dependent PDEs. SIAM/ASA J. Uncertainty Quantification, 3(1):852–872, 2015. (PDF, 330 kB)

[32]
D. Kressner, R. Kumar, F. Nobile, and C. Tobler. Low-rank tensor approximation for high-order correlation functions of Gaussian random fields. SIAM/ASA J. Uncertain. Quantif., 3(1):393–416, 2015. (PDF, 590 kB)

[33]
Z. Bujanović and D. Kressner. A block algorithm for computing antitriangular factorizations of symmetric matrices. Numer. Algorithms, 71(1):41–57, 2016. (PDF, 346 kB)

[34]
D. Kressner and P. Sirković. Truncated low-rank methods for solving general linear matrix equations. Numer. Linear Algebra Appl., 22(3):564–583, 2015. (PDF, 580 kB)

[35]
R. Schneider and A. Uschmajew. Convergence results for projected line-search methods on varieties of low-rank matrices via Ł ojasiewicz inequality. SIAM J. Optim., 25(1):622–646, 2015. (PDF, 485 kB)

[36]
Z. Li, A. Uschmajew, and S. Zhang. On convergence of the maximum block improvement method. SIAM J. Optim., 25(1):210–233, 2015. (PDF, 1589 kB)

[37]
N. Guglielmi, D. Kressner, and C. Lubich. Low-rank differential equations for Hamiltonian matrix nearness problems. Numer. Math., 129(2):279–319, 2015. (PDF, 407 kB)

[38]
R. Andreev and C. Tobler. Multilevel preconditioning and low-rank tensor iteration for space-time simultaneous discretizations of parabolic PDEs. Numer. Linear Algebra Appl., 22(2):317–337, 2015. (PDF, 539 kB)

[39]
R. Granat, B. Kågström, D. Kressner, and M. Shao. Algorithm 953: parallel library software for the multishift QR algorithm with aggressive early deflation. ACM Trans. Math. Software, 41(4):Art. 29, 23, 2015. (PDF, 252 kB)

[40]
N. Guglielmi, D. Kressner, and C. Lubich. Computing extremal points of symplectic pseudospectra and solving symplectic matrix nearness problems. SIAM J. Matrix Anal. Appl., 35(4):1407–1428, 2014. (PDF, 411 kB)

[41]
W. G. Vandenberghe, M. V. Fischetti, R. Beeumen, K. Meerbergen, W. Michiels, and C. Effenberger. Determining Bound States in a Semiconductor Device with Contacts Using a Nonlinear Eigenvalue Solver. J. Comput. Electron., 13(3):753–762, 2014.

[42]
L. Grubišić and D. Kressner. On the eigenvalue decay of solutions to operator Lyapunov equations. Systems & Control Letters, 73:42–47, 2014. (PDF, 357 kB)

[43]
D. Kressner, M. Steinlechner, and A. Uschmajew. Low-rank tensor methods with subspace correction for symmetric eigenvalue problems. SIAM J. Sci. Comput., 36(5):A2346–A2368, 2014. (PDF, 372 kB)

[44]
B. Adlerborn, B. Kågström, and D. Kressner. A parallel QZ algorithm for distributed memory HPC systems. SIAM J. Sci. Comput., 36(5):C480–C503, 2014. (PDF, 667 kB)

[45]
M. Shao. On the finite section method for computing exponentials of doubly-infinite skew-Hermitian matrices. Linear Algebra Appl., 451:65–96, 2014. (PDF, 2483 kB)

[46]
M. Karow, D. Kressner, and E. Mengi. Nonlinear eigenvalue problems with specified eigenvalues. SIAM J. Matrix Anal. Appl., 35(3):819–834, 2014. (PDF, 421 kB)

[47]
M. Karow and D. Kressner. On a Perturbation Bound for Invariant Subspaces of Matrices. SIAM J. Matrix Anal. Appl., 35(2):599–618, 2014. (PDF, 392 kB)

[48]
D. Kressner and B. Vandereycken. Subspace methods for computing the pseudospectral abscissa and the stability radius. SIAM J. Matrix Anal. Appl., 35(1):292–313, 2014. (PDF, 588 kB)

[49]
D. Kressner and C. Tobler. Algorithm 941: htucker—A Matlab Toolbox for Tensors in Hierarchical Tucker Format. ACM Trans. Math. Softw., 40(3):Art. 22, 22, 2014. (PDF, 556 kB)

[50]
D. Kressner, M. Steinlechner, and B. Vandereycken. Low-rank tensor completion by Riemannian optimization. BIT, 54(2):447–468, 2014. (PDF, 1536 kB)

[51]
R. Schneider and A. Uschmajew. Approximation rates for the hierarchical tensor format in periodic Sobolev spaces. J. Complexity, 30(2):56–71, 2014. (PDF, 192 kB)

[52]
L. Karlsson, D. Kressner, and B. Lang. Optimally packed chains of bulges in multishift QR algorithms. ACM Trans. Math. Software, 40(2):Art. 12, 15, 2014. (PDF, 412 kB)

[53]
D. Kressner, E. Mengi, I. Nakic, and N. Truhar. Generalized eigenvalue problems with specified eigenvalues. IMA J. Numer. Anal., 34(2):480–501, 2014. (PDF, 375 kB)

[54]
D. Kressner. Bivariate matrix functions. Oper. Matrices, 8(2):449–466, 2014. (PDF, 202 kB)

[55]
D. Kressner and J. E. Roman. Memory-efficient Arnoldi algorithms for linearizations of matrix polynomials in Chebyshev basis. Numer. Linear Algebra Appl., 21(4):569–588, 2014. (PDF, 277 kB)

[56]
D. Kressner, M. Miloloža Pandur, and M. Shao. An indefinite variant of LOBPCG for definite matrix pencils. Numer. Algorithms, 66(4):681–703, 2014. (PDF, 542 kB)

[57]
D. Kressner, M. Plešinger, and C. Tobler. A preconditioned low-rank CG method for parameter-dependent Lyapunov matrix equations. Numer. Linear Algebra Appl., 21(5):666–684, 2014. (PDF, 529 kB)

[58]
B. Beckermann, D. Kressner, and C. Tobler. An error analysis of Galerkin projection methods for linear systems with tensor product structure. SIAM J. Numer. Anal., 51(6):3307–3326, 2013. (PDF, 455 kB)

[59]
C. Lubich, T. Rohwedder, R. Schneider, and B. Vandereycken. Dynamical Approximation by Hierarchical Tucker and Tensor-Train Tensors. SIAM J. Matrix Anal. Appl., 34(2):470–494, 2013. (PDF, 540 kB)

[60]
B. Vandereycken. Low-rank Matrix Completion by Riemannian Optimization. SIAM J. Optim., 23(2):1214–1236, 2013. (PDF, 814 kB)

[61]
L. Grasedyck, D. Kressner, and C. Tobler. A literature survey of low-rank tensor approximation techniques. GAMM-Mitt., 36(1):53–78, 2013. (PDF, 474 kB)

[62]
C. Effenberger. Robust successive computation of eigenpairs for nonlinear eigenvalue problems. SIAM J. Matrix Anal. Appl., 34(3):1231–1256, 2013. (PDF, 383 kB)

[63]
D. Kressner and X. Liu. Structured canonical forms for products of (skew-)symmetric matrices and the matrix equation XAX = B. Electron. J. Linear Algebra, 26:215–230, 2013. (PDF, 332 kB)

[64]
A. Uschmajew and B. Vandereycken. The geometry of algorithms using hierarchical tensors. Linear Algebra Appl., 439(1):133–166, 2013. (PDF, 321 kB)

[65]
B. Jeuris, R. Vandebril, and B. Vandereycken. A survey and comparison of contemporary algorithms for computing the matrix geometric mean. Electron. Trans. Numer. Anal., 39:379–402, 2012. (PDF, 409 kB)

[66]
C. Effenberger and D. Kressner. Chebyshev interpolation for nonlinear eigenvalue problems. BIT, 52(4):933–951, 2012. DOI: 10.1007/s10543-012-0381-5. (PDF, 413 kB)

[67]
C. Effenberger, D. Kressner, and C. Engström. Linearization techniques for band structure calculations in absorbing photonic crystals. Int. J. Numer. Meth. Eng., 89(2):180–191, 2012. (PDF, 427 kB)

[68]
D. Kressner and C. Tobler. Preconditioned low-rank methods for high-dimensional elliptic PDE eigenvalue problems. Comput. Methods Appl. Math., 11(3):363–381, 2011. (PDF, 685 kB)

[69]
D. Kressner and C. Tobler. Low-rank tensor Krylov subspace methods for parameterized linear systems. SIAM J. Matrix Anal. Appl., 32(4):1288–1316, 2011. (PDF, 1647 kB)

[70]
W.-J. Beyn, C. Effenberger, and D. Kressner. Continuation of eigenvalues and invariant pairs for parameterized nonlinear eigenvalue problems. Numer. Math., 119(3):489–516, 2011. (PDF, 692 kB)

[71]
B. Adhikari, R. Alam, and D. Kressner. Structured eigenvalue condition numbers and linearizations for matrix polynomials. Linear Algebra Appl., 435(9):2193–2221, 2011. (PDF, 326 kB)

[72]
B. Kågström, L. Karlsson, and D. Kressner. Computing codimensions and generic canonical forms for generalized matrix products. Electron. J. Linear Algebra, 22:277–309, 2011. (PDF, 347 kB)

[73]
P. Benner, P. Ezzatti, D. Kressner, E.S. Quintana-Ortí, and A. Remón. A mixed-precision algorithm for the solution of Lyapunov equations on hybrid CPU-GPU platforms. Parallel Computing, 37(8):439 – 450, 2011. (PDF, 286 kB)

[74]
E. Kokiopoulou, D. Kressner, and P. Frossard. Optimal image alignment with random projections of manifolds: algorithm and geometric analysis. IEEE Transactions on Image Processing, 20:1543–1557, 2011. (PDF, 501 kB)

[75]
P. Bientinesi, F. D. Igual, D. Kressner, M. Petschow, and E. S. Quintana-Ortí. Condensed forms for the symmetric eigenvalue problem on multi-threaded architectures. Concurrency and Computation: Practice and Experience, 23(7):694–707, 2011. (PDF, 281 kB)

[76]
R. Granat, B. Kågström, and D. Kressner. A novel parallel QR algorithm for hybrid distributed memory HPC systems. SIAM J. Sci. Comput., 32(4):2345–2378, 2010. (PDF, 423 kB)

[77]
T. Betcke and D. Kressner. Perturbation, Extraction and Refinement of Invariant Pairs for Matrix Polynomials. Linear Algebra Appl., 435(3):514–536, 2011. (PDF, 306 kB)

[78]
D. Kressner and C. Tobler. Krylov subspace methods for linear systems with tensor product structure. SIAM J. Matrix Anal. Appl., 31(4):1688–1714, 2010. (PDF, 348 kB)

[79]
M. Karow, E. Kokiopoulou, and D. Kressner. On the computation of structured singular values and pseudospectra. Systems Control Lett., 59(2):122–129, 2010. (PDF, 394 kB)

[80]
P. Benner, D. Kressner, V. Sima, and A. Varga. Die SLICOT-Toolboxen für Matlab. Automatisierungstechnik, 58(1):15–25, 2010. (PDF, 242 kB)

[81]
D. Kressner. A block Newton method for nonlinear eigenvalue problems. Numer. Math., 114(2):355–372, 2009. (PDF, 190 kB)

[82]
D. Kressner, M. J. Peláez, and J. Moro. Structured Hölder condition numbers for multiple eigenvalues. SIAM J. Matrix Anal. Appl., 31(1):175–201, 2009. (PDF, 306 kB)

[83]
M. Karow and D. Kressner. On the structured distance to uncontrollability. Systems Control Lett., 58(2):128–132, 2009. (PostScript, 11 pages, 345 kB) (PDF, 197 kB)

[84]
R. Granat, B. Kågström, and D. Kressner. Parallel eigenvalue reordering in real Schur forms. Concurrency and Computation: Practice and Experience, 21(9):1225–1250, 2009. (PDF, 341 kB)

[85]
D. Kressner, C. Schröder, and D. S. Watkins. Implicit QR algorithms for palindromic and even eigenvalue problems. Numerical Algorithms, 51(2):209–238, 2009. Also appeared as DFG research center Matheon preprint 432. (PDF, 341 kB)

[86]
B. Kågström, D. Kressner, E. Quintana-Orti, and G. Quintana-Orti. Blocked algorithms for the reduction to Hessenberg-triangular form revisited. BIT, 48(3):563–584, 2008. Also appeared as LAPACK working note 198. (Gzipped PostScript, 20 pages, 227 kB) (PDF, 263 kB)

[87]
D. Kressner. The effect of aggressive early deflation on the convergence of the QR algorithm. SIAM J. Matrix Anal. Appl., 30(2):805–821, 2008. (Gzipped PostScript, 19 pages, 204 kB) (PDF, 249 kB)

[88]
D. Kressner. Block variants of Hammarling's method for solving Lyapunov equations. ACM Trans. Math. Software, 34(1):1–15, 2008. (Gzipped PostScript, 15 pages, 201 kB) (PDF, 215 kB)

[89]
D. Kressner. Deflation in Krylov subspace methods and distance to uncontrollability. Annali dell'Universita di Ferrara, 53:309–318, 2007. (Gzipped PostScript, 10 pages, 151 kB) (PDF, 235 kB)

[90]
R. Granat, B. Kågström, and D. Kressner. Computing Periodic Deflating Subspaces Associated with a Specified Set of Eigenvalues. BIT, 47(4):763–791, 2007. (PDF, 796 kB)

[91]
B. Kågström and D. Kressner. Multishift variants of the QZ algorithm with aggressive early deflation. SIAM J. Matrix Anal. Appl., 29(1):199–227, 2006. Also appeared as LAPACK working note 173. (Gzipped PostScript, 44 pages, 380 kB) (PDF, 597 kB)

[92]
M. Karow, D. Kressner, and F. Tisseur. Structured Eigenvalue Condition Numbers. SIAM J. Matrix Anal. Appl., 28(4):1052–1068, 2006. (PDF, 218 kB)

[93]
D. Kressner. Block Algorithms for Reordering Standard and Generalized Schur Forms. ACM Trans. Math. Software, 32(4):521–532, 2006. Also appeared as LAPACK working note 171. (Gzipped PostScript, 11 pages, 206 kB) (PDF, 169 kB)

[94]
P. Benner and D. Kressner. Algorithm 854: Fortran 77 Subroutines for Computing the Eigenvalues of Hamiltonian Matrices II. ACM Trans. Math. Software, 32(2):352–373, 2006. (Gzipped PostScript, 25 pages, 261 kB) (PDF, 252 kB)

[95]
D. Kressner. A Periodic Krylov-Schur Algorithm for Large Matrix Products. Numer. Math., 103(3):461–483, 2006. (Gzipped PostScript, 27 pages, 233 kB) (PDF, 220 kB)

[96]
R. Byers and D. Kressner. Structured Condition Numbers for Invariant Subspaces. SIAM J. Matrix Anal. Appl., 28(2):326–347, 2006. (Gzipped PostScript, 23 pages, 243 kB) (PDF, 305 kB)

[97]
D. Kressner. The Periodic QR Algorithm is a Disguised QR Algorithm. Linear Algebra Appl., 417(2–3):423–433, 2006. (Gzipped PostScript, 12 pages, 151 kB)

[98]
P. Benner and D. Kressner. Balancing Sparse Hamiltonian Eigenproblems. Linear Algebra Appl., 415(1):3–19, 2006. (Gzipped PostScript, 15 pages, 182 kB)

[99]
H. Faßbender and D. Kressner. Structured Eigenvalue Problems. GAMM Mitteilungen 29, Themenheft Applied and Numerical Linear Algebra, Part II:297–318, 2006. (PDF, 231 kB)

[100]
A. Griewank and D. Kressner. Time-lag in Derivative Convergence for Fixed Point Iterations. Revue ARIMA, Spécial CARI'04:87–102, 2005. (PDF, 282 kB)

[101]
D. Kressner. On the Use of Larger Bulges in the QR Algorithm. Electron. Trans. Numer. Anal., 20:50–63, 2005. (Gzipped PostScript, 14 pages, 245 kB) (PDF, 317 kB)

[102]
D. Kressner. Perturbation Bounds for Isotropic Invariant Subspaces of Skew-Hamiltonian Matrices. SIAM J. Matrix Anal. Appl., 26(4):947–961, 2005. (Gzipped PostScript, 15 pages, 205 kB)

[103]
R. Byers and D. Kressner. On the Condition of a Complex Eigenvalue under Real Perturbations. BIT, 44(2):209–215, 2004. (Gzipped PostScript, 6 pages, 159 kB) (PDF, 186 kB)

[104]
D. Kressner. Block Algorithms for Orthogonal Symplectic Factorizations. BIT, 43(4):775–790, 2003. (Gzipped PostScript, 16 pages, 203 kB)

[105]
P. Benner, D. Kressner, and V. Mehrmann. Structure Preservation: A Challenge in Computational Control. Future Generation Computer Systems, 19(7):1243–1252, 2003. (Gzipped PostScript, 15 pages, 189 kB)

[106]
N. Mastronardi, D. Kressner, V. Sima, P. Van Dooren, and S. Van Huffel. A fast algorithm for subspace state-space system identification via exploitation of the displacement structure. J. Comput. Appl. Math., 132(1):71–81, 2001. Advanced numerical methods for mathematical modelling. (Gzipped PostScript, 15 pages, 102 kB)

Book chapters

[1]
P. Benner, D. Kressner, and V. Mehrmann. Skew-Hamiltonian and Hamiltonian Eigenvalue Problems: Theory, Algorithms and Applications. In Z. Drmač, M. Marušić, and Z. Tutek, editors, Proceedings of the Conference on Applied Mathematics and Scientific Computing, Brijuni (Croatia), June 23-27, 2003, pages 3–39. Springer-Verlag, 2005. (Gzipped PostScript, 41 pages, 284 kB) (PDF, 364 kB)

[2]
D. Kressner and M. Voigt. Distance problems for linear dynamical systems. In Benner et al., editor, Numerical Algebra, Matrix Theory, Differential-Algebraic Equations and Control Theory – Festschrift in Honor of Volker Mehrmann, 2015. (PDF, 276 kB)

[3]
J. Ballani and D. Kressner. Matrices with hierarchical low-rank structure. In Benzi et al., editor, CIME Summer School on Exploiting Hidden Structure in Matrix Computations, 2016. To appear. (PDF, 939 kB)

Articles in conference proceedings

[1]
F. Macedo. Finding steady states of communicating Markov processes combining aggregation/disaggregation with tensor techniques. Technical report, August 2016. Accepted for EPEW 2016 – 13th European Workshop on Performance Engineering. (PDF, 351 kB)

[2]
D. Kressner and F. Macedo. Low-rank tensor methods for communicating Markov processes. Technical report, March 2014. Accepted for QEST 2014 – 11th International Conference on Quantitative Evaluation of SysTems. (PDF, 362 kB)

[3]
D. Kressner, P. Sirkovic, N. T. Son, and T. Stykel. A low-rank reduced basis method for parameter-dependent Lyapunov equations. Technical report, December 2013. Accepted for MTNS 2014 – 21st International Symposium on Mathematical Theory of Networks and Systems. (PDF, 216 kB)

[4]
P. Benner, D. Kressner, and V. Sima. New SLICOT routines based on structured eigensolvers. In 2012 IEEE International Conference on Control Applications (CCA), pages 640–645, 2012. (PDF, 144 kB)

[5]
C. Effenberger, D. Kressner, O. Steinbach, and G. Unger. Interpolation-based solution of a nonlinear eigenvalue problem in fluid-structure interaction. In Proceedings in Applied Mathematics and Mechanics, volume 12, pages 633–634, 2012. DOI: 10.1002/pamm.201210305. (PDF, 246 kB)

[6]
H. Papasaika, E. Kokiopoulou, E. Baltsavias, K. Schindler, and D. Kressner. Fusion of Digital Elevation Models Using Sparse Representations. In Photogrammetric Image Analysis, volume 6952 of Lecture Notes in Computer Science, pages 171–184. Springer Berlin / Heidelberg, 2011. (PDF, 540 kB)

[7]
E. Kokiopoulou, M. Zervos, D. Kressner, and N. Paragios. Optimal similarity registration of volumetric images. In Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on, pages 2449 –2456, june 2011. (PDF, 326 kB)

[8]
P. Benner, P. Ezzatti, D. Kressner, E. S. Quintana-Ortí, and A. Remón. Accelerating Model Reduction of Large Linear Systems with Graphics Processors, September 2010. (PDF, 332 kB)

[9]
B. Kågström, D. Kressner, and M. Shao. On aggressive early deflation in parallel variants of the QR algorithm. In Proceedings of PARA2010, Reykjavik, Iceland, September 2010. (PDF, 129 kB)

[10]
P. Bientinesi, F. D. Igual, D. Kressner, and E. S. Quintana-Ortí. Reduction to condensed forms for symmetric eigenvalue problems on multi-core architectures. In Proceedings of Eighth International Conference on Parallel Processing and Applied Mathematics (PPAM 2009), 2009. (PDF, 243 kB)

[11]
E. Kokiopoulou, D. Kressner, and P. Frossard. Optimal image alignment with random measurements. In Proceedings of 17th European Signal Processing Conference (EUSIPCO), 2009. (PDF, 144 kB)

[12]
D. Kressner. Memory-efficient Krylov subspace techniques for solving large-scale Lyapunov equations. In IEEE International Symposium on Computer-Aided Control Systems Design, San Antonio, pages 613–618, 2008. (Gzipped PostScript, 6 pages, 103 kB) (PDF, 124 kB)

[13]
R. Granat, B. Kågström, and D. Kressner. A parallel Schur method for solving continuous-time algebraic Riccati equations. In IEEE International Symposium on Computer-Aided Control Systems Design, San Antonio, pages 583–588, 2008. (PDF, 220 kB)

[14]
R. Granat, B. Kågström, and D. Kressner. Matlab tools for solving periodic eigenvalue problems. In G. Leonov and A. Fradkov, editors, Third IFAC Workshop on Periodic Control Systems, 2007. (PDF, 155 kB)

[15]
B. Adlerborn, B. Kågström, and D. Kressner. Parallel Variants of the Multishift QZ Algorithm with Advanced Deflation Techniques. In Proceedings of PARA06, Umeå, Sweden, 2006. (PDF, 173 kB)

[16]
D. Kressner and E. Mengi. Structure-preserving eigenvalue solvers for robust stability and controllability estimates. In Proceedings of 45th IEEE Conference on Decision and Control, 2006. (PDF, 331 kB)

[17]
R. Granat, B. Kågström, and D. Kressner. Reordering the Eigenvalues of a Periodic Matrix Pair with Applications in Control. In IEEE International Symposium on Computer-Aided Control Systems Design, Munich, 2006. (Gzipped PostScript, 6 pages, 87 kB) (PDF, 104 kB)

[18]
D. Kressner. Finding the Distance to Instability of a Large Sparse Matrix. In IEEE International Symposium on Computer-Aided Control Systems Design, Munich, 2006. To appear. (Gzipped PostScript, 5 pages, 92 kB) (PDF, 108 kB)

[19]
P. Benner and D. Kressner. New Hamiltonian Eigensolvers with Applications in Control. In Proceedings of 44th IEEE Conference on Decision and European Control Conference ECC 2005, pages 6551–6556, 2005. (Gzipped PostScript, 6 pages, 104 kB) (PDF, 209 kB)

[20]
D. Kressner. Large Periodic Lyapunov Equations: Algorithms and Applications. In Proc. of ECC'03, Cambridge, UK, 2003. (PDF, 87 kB)

[21]
P. Johansson and D. Kressner. Semi-Automatic Generation of Web-Based Computing Environments for Software Libraries. In P.M.A. Sloot et al., editor, ICCS 2002, LNCS 2329, pages 872–880. Springer-Verlag, 2002. (Gzipped PostScript, 9 pages, 134 kB)

[22]
D. Kressner. An efficient and reliable implementation of the periodic QZ algorithm. In IFAC Workshop on Periodic Control Systems, 2001. (Gzipped PostScript, 6 pages, 92 kB)

[23]
E. Elmroth, P. Johansson, B. Kågström, and D. Kressner. A Web Computing Environment for the SLICOT Library. In The Third NICONET Workshop on Numerical Control Software, pages 53–61, 2001. (Gzipped PostScript, 11 pages, 245 kB)

Software reports and miscellaneous

[1]
A. Šušnjara, N. Perraudin, D. Kressner, and P. Vandergheynst. Accelerated filtering on graphs using Lanczos method. Technical report, September 2015. (PDF, 409 kB)

[2]
F. Macedo. Benchmark Problems on Stochastic Automata Networks in Tensor Train Format. Technical report, September 2015. (PDF, 568 kB)

[3]
J. Ballani and D. Kressner. Sparse inverse covariance estimation with hierarchical matrices. Technical report, October 2014. (PDF, 396 kB)

[4]
C. Effenberger and D. Kressner. On the residual inverse iteration for nonlinear eigenvalue problems admitting a Rayleigh functional. Technical report, January 2014. (PDF, 332 kB)

[5]
D. Kressner and C. Tobler. htucker - A Matlab toolbox for the hierarchical Tucker format. Technical report, August 2012. Extended version. (PDF, 2933 kB)

[6]
E. Kokiopoulou, D. Kressner, and Y. Saad. Linear dimension reduction for evolutionary data. Technical report, December 2010. (PDF, 413 kB)

[7]
P. Benner, D. Kressner, and V. Sima. The SLICOT Toolboxes - a Survey. (PDF, 196 kB)

[8]
D. Kressner and P. Van Dooren. Factorizations and linear system solvers for matrices with Toeplitz structure. SLICOT working note 2000-2, WGS, June 2000. updated June 2001. (Gzipped PostScript, 19 pages, 105 kB)

[9]
D. Kressner, V. Mehrmann, and T. Penzl. DTLEX - a Collection of Benchmark Examples for Discrete-Time Lyapunov Equations. SLICOT working note 1999-7, WGS, 1999. (Gzipped PostScript, 17 pages, 186 kB)

[10]
D. Kressner, V. Mehrmann, and T. Penzl. CTLEX - a Collection of Benchmark Examples for Continuous-Time Lyapunov Equations. SLICOT working note 1999-6, WGS, 1999. (Gzipped PostScript, 16 pages, 186 kB)

[11]
D. Kressner, V. Mehrmann, and T. Penzl. DTDSX - a Collection of Benchmark Examples for State-Space Realizations of Discrete-Time Dynamical Systems. SLICOT working note 1998-10, WGS, 1998. (Gzipped PostScript, 17 pages, 186 kB)

[12]
D. Kressner, V. Mehrmann, and T. Penzl. CTDSX - a Collection of Benchmark Examples for State-Space Realizations of Continuous-Time Dynamical Systems. SLICOT working note 1998-9, WGS, 1998. (Gzipped PostScript, 33 pages, 89 kB)