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ORCIDMichiel E. Hochstenbach
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2020 – today
- 2025
[j36]Perfect Y. Gidisu
, Michiel E. Hochstenbach:
Block discrete empirical interpolation methods. J. Comput. Appl. Math. 454: 116186 (2025)- 2024
- [j35]Giulia Ferrandi, Michiel E. Hochstenbach:
A homogeneous Rayleigh quotient with applications in gradient methods. J. Comput. Appl. Math. 437: 115440 (2024) - [j34]Lu Xia, Stefano Massei, Michiel E. Hochstenbach, Barry Koren:
On Stochastic Roundoff Errors in Gradient Descent with Low-Precision Computation. J. Optim. Theory Appl. 200(2): 634-668 (2024) - [j33]Michiel E. Hochstenbach, Tomaz Kosir, Bor Plestenjak:
Numerical methods for rectangular multiparameter eigenvalue problems, with applications to finding optimal ARMA and LTI models. Numer. Linear Algebra Appl. 31(2) (2024) - [j32]Perfect Y. Gidisu, Michiel E. Hochstenbach:
A Restricted SVD Type CUR Decomposition for Matrix Triplets. SIAM J. Sci. Comput. 46(2): S401-S423 (2024) - [i19]Giulia Ferrandi, Michiel E. Hochstenbach, M. R. Oliveira:
A subspace method for large-scale trace ratio problems. CoRR abs/2402.02920 (2024) - [i18]Michiel E. Hochstenbach, Christian Mehl, Bor Plestenjak:
Solving singular generalized eigenvalue problems. Part III: structure preservation. CoRR abs/2406.07109 (2024) - [i17]Michiel E. Hochstenbach, Christian Mehl, Bor Plestenjak:
Numerical methods for eigenvalues of singular polynomial eigenvalue problems. CoRR abs/2406.16832 (2024) - 2023
- [j31]Giulia Ferrandi, Michiel E. Hochstenbach, Natasa Krejic:
A harmonic framework for stepsize selection in gradient methods. Comput. Optim. Appl. 85(1): 75-106 (2023) - [j30]Michiel E. Hochstenbach, Christian Mehl, Bor Plestenjak:
Solving Singular Generalized Eigenvalue Problems. Part II: Projection and Augmentation. SIAM J. Matrix Anal. Appl. 44(4): 1589-1618 (2023) - [i16]Lu Xia, Michiel E. Hochstenbach, Stefano Massei:
On the Convergence of the Gradient Descent Method with Stochastic Fixed-point Rounding Errors under the Polyak-Lojasiewicz Inequality. CoRR abs/2301.09511 (2023) - [i15]Giulia Ferrandi, Michiel E. Hochstenbach:
Limited memory gradient methods for unconstrained optimization. CoRR abs/2308.15145 (2023) - [i14]Perfect Y. Gidisu, Michiel E. Hochstenbach:
A DEIM-CUR factorization with iterative SVDs. CoRR abs/2310.00636 (2023) - 2022
- [j29]Perfect Y. Gidisu, Michiel E. Hochstenbach:
A Generalized CUR Decomposition for Matrix Pairs. SIAM J. Math. Data Sci. 4(1): 386-409 (2022) - [i13]Perfect Y. Gidisu, Michiel E. Hochstenbach:
A hybrid DEIM and leverage scores based method for CUR index selection. CoRR abs/2201.07017 (2022) - [i12]Giulia Ferrandi, Michiel E. Hochstenbach, Natasa Krejic:
A harmonic framework for stepsize selectionin gradient methods. CoRR abs/2202.10213 (2022) - [i11]Lu Xia, Stefano Massei, Michiel E. Hochstenbach, Barry Koren:
On the influence of roundoff errors on the convergence of the gradient descent method with low-precision floating-point computation. CoRR abs/2202.12276 (2022) - [i10]Perfect Y. Gidisu, Michiel E. Hochstenbach:
RSVD-CUR Decomposition for Matrix Triplets. CoRR abs/2204.02113 (2022) - [i9]Giulia Ferrandi, Michiel E. Hochstenbach:
A homogeneous Rayleigh quotient with applications in gradient methods. CoRR abs/2206.13457 (2022) - [i8]Michiel E. Hochstenbach, Christian Mehl, Bor Plestenjak:
Solving singular generalized eigenvalue problems. Part II: projection and augmentation. CoRR abs/2208.01359 (2022) - [i7]Perfect Y. Gidisu, Michiel E. Hochstenbach:
Block Discrete Empirical Interpolation Methods. CoRR abs/2208.02213 (2022) - [i6]Giulia Ferrandi, Igor V. Kravchenko, Michiel E. Hochstenbach, M. Rosário Oliveira:
On the trace ratio method and Fisher's discriminant analysis for robust multigroup classification. CoRR abs/2211.08120 (2022) - [i5]Michiel E. Hochstenbach, Tomaz Kosir, Bor Plestenjak:
On the solution of rectangular multiparameter eigenvalue problems. CoRR abs/2212.01867 (2022) - 2021
- [j28]Sibylle Hess, Gianvito Pio, Michiel E. Hochstenbach, Michelangelo Ceci:
BROCCOLI: overlapping and outlier-robust biclustering through proximal stochastic gradient descent. Data Min. Knowl. Discov. 35(6): 2542-2576 (2021) - [j27]Bart S. van Lith, Per Christian Hansen, Michiel E. Hochstenbach:
A Twin Error Gauge for Kaczmarz's Iterations. SIAM J. Sci. Comput. 43(5): S173-S199 (2021) - [i4]Lu Xia, Martijn Anthonissen, Michiel E. Hochstenbach, Barry Koren:
A Simple and Efficient Stochastic Rounding Method for Training Neural Networks in Low Precision. CoRR abs/2103.13445 (2021) - [i3]Perfect Y. Gidisu, Michiel E. Hochstenbach:
A Generalized CUR decomposition for matrix pairs. CoRR abs/2107.03126 (2021) - 2020
- [i2]Lu Xia, Martijn Anthonissen, Michiel E. Hochstenbach, Barry Koren:
Improved stochastic rounding. CoRR abs/2006.00489 (2020)
2010 – 2019
- 2019
- [j26]Michiel E. Hochstenbach, Karl Meerbergen, Emre Mengi, Bor Plestenjak:
Subspace methods for three-parameter eigenvalue problems. Numer. Linear Algebra Appl. 26(4) (2019) - [j25]Michiel E. Hochstenbach, Christian Mehl, Bor Plestenjak:
Solving Singular Generalized Eigenvalue Problems by a Rank-Completing Perturbation. SIAM J. Matrix Anal. Appl. 40(3): 1022-1046 (2019) - [j24]Yiqiu Dong, Per Christian Hansen, Michiel E. Hochstenbach, Nicolai André Brogaard Riis:
Fixing Nonconvergence of Algebraic Iterative Reconstruction with an Unmatched Backprojector. SIAM J. Sci. Comput. 41(3): A1822-A1839 (2019) - [i1]Bart S. van Lith, Per Christian Hansen, Michiel E. Hochstenbach:
A twin error gauge for Kaczmarz's iterations. CoRR abs/1906.07470 (2019) - 2017
- [j23]Ian N. Zwaan, Michiel E. Hochstenbach:
Multidirectional Subspace Expansion for One-Parameter and Multiparameter Tikhonov Regularization. J. Sci. Comput. 70(3): 990-1009 (2017) - [j22]Ada Boralevi, Jasper van Doornmalen, Jan Draisma, Michiel E. Hochstenbach, Bor Plestenjak:
Uniform Determinantal Representations. SIAM J. Appl. Algebra Geom. 1(1): 415-441 (2017) - [j21]Ian N. Zwaan, Michiel E. Hochstenbach:
Krylov-Schur-Type Restarts for the Two-Sided Arnoldi Method. SIAM J. Matrix Anal. Appl. 38(2): 297-321 (2017) - 2016
- [j20]Antti Koskela, Elias Jarlebring, Michiel E. Hochstenbach:
Krylov Approximation of Linear ODEs with Polynomial Parameterization. SIAM J. Matrix Anal. Appl. 37(2): 519-538 (2016) - [j19]Bor Plestenjak, Michiel E. Hochstenbach:
Roots of Bivariate Polynomial Systems via Determinantal Representations. SIAM J. Sci. Comput. 38(2) (2016) - 2015
- [j18]Michiel E. Hochstenbach, Lothar Reichel, Giuseppe Rodriguez:
Regularization parameter determination for discrete ill-posed problems. J. Comput. Appl. Math. 273: 132-149 (2015) - [j17]Michiel E. Hochstenbach, Andrej Muhic, Bor Plestenjak:
Jacobi-Davidson methods for polynomial two-parameter eigenvalue problems. J. Comput. Appl. Math. 288: 251-263 (2015) - [j16]Bor Plestenjak, Calin-Ioan Gheorghiu, Michiel E. Hochstenbach:
Spectral collocation for multiparameter eigenvalue problems arising from separable boundary value problems. J. Comput. Phys. 298: 585-601 (2015) - [j15]Michiel E. Hochstenbach, Lothar Reichel, Xuebo Yu:
A Golub-Kahan-Type Reduction Method for Matrix Pairs. J. Sci. Comput. 65(2): 767-789 (2015) - [j14]Sarah W. Gaaf, Michiel E. Hochstenbach:
Probabilistic Bounds for the Matrix Condition Number with Extended Lanczos Bidiagonalization. SIAM J. Sci. Comput. 37(5) (2015) - 2013
- [j13]Ivo W. M. Bleylevens, Michiel E. Hochstenbach, Ralf L. M. Peeters:
Polynomial optimization and a Jacobi-Davidson type method for commuting matrices. Appl. Math. Comput. 224: 564-580 (2013) - [j12]Michiel E. Hochstenbach:
Probabilistic Upper Bounds for the Matrix Two-Norm. J. Sci. Comput. 57(3): 464-476 (2013) - 2012
- [j11]Calin-Ioan Gheorghiu, Michiel E. Hochstenbach, Bor Plestenjak, Joost Rommes:
Spectral collocation solutions to multiparameter Mathieu's system. Appl. Math. Comput. 218(24): 11990-12000 (2012) - [j10]Michiel E. Hochstenbach, Lothar Reichel:
Combining approximate solutions for linear discrete ill-posed problems. J. Comput. Appl. Math. 236(8): 2179-2185 (2012) - 2010
- [j9]Michiel E. Hochstenbach, Lothar Reichel:
Subspace-restricted singular value decompositions for linear discrete ill-posed problems. J. Comput. Appl. Math. 235(4): 1053-1064 (2010)
2000 – 2009
- 2009
- [j8]Michiel E. Hochstenbach, Yvan Notay:
Controlling Inner Iterations in the Jacobi-Davidson Method. SIAM J. Matrix Anal. Appl. 31(2): 460-477 (2009) - 2008
- [j7]Michiel E. Hochstenbach, Gerard L. G. Sleijpen:
Harmonic and refined Rayleigh-Ritz for the polynomial eigenvalue problem. Numer. Linear Algebra Appl. 15(1): 35-54 (2008) - 2004
- [j6]Michiel E. Hochstenbach, Tomaz Kosir, Bor Plestenjak:
A Jacobi-Davidson Type Method for the Two-Parameter Eigenvalue Problem. SIAM J. Matrix Anal. Appl. 26(2): 477-497 (2004) - [j5]Peter Arbenz, Michiel E. Hochstenbach:
A Jacobi-Davidson Method for Solving Complex Symmetric Eigenvalue Problems. SIAM J. Sci. Comput. 25(5): 1655-1673 (2004) - 2003
- [j4]Michiel E. Hochstenbach, Henk A. van der Vorst:
Alternatives to the Rayleigh Quotient for the Quadratic Eigenvalue Problem. SIAM J. Sci. Comput. 25(2): 591-603 (2003) - 2002
- [j3]Michiel E. Hochstenbach, Bor Plestenjak:
A Jacobi-Davidson Type Method for a Right Definite Two-Parameter Eigenvalue Problem. SIAM J. Matrix Anal. Appl. 24(2): 392-410 (2002) - 2001
- [j2]Jos L. M. van Dorsselaer, Michiel E. Hochstenbach, Henk A. van der Vorst:
Computing Probabilistic Bounds for Extreme Eigenvalues of Symmetric Matrices with the Lanczos Method. SIAM J. Matrix Anal. Appl. 22(3): 837-852 (2001) - [j1]Michiel E. Hochstenbach:
A Jacobi-Davidson Type SVD Method. SIAM J. Sci. Comput. 23(2): 606-628 (2001)
Coauthor Index
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