Fast algorithms for exponential data modeling. - Haesun Park; Sabine Van Huffel; Lars Eldén (ICASSP (4), 1994)

Accurate Downdating of Least Squares Solutions. - Åke Björck; Haesun Park; Lars Eldén (SIAM J. Matrix Anal. Appl., 1994)

Block Downdating of Least Squares Solutions. - Lars Eldén; Haesun Park (SIAM J. Matrix Anal. Appl., 1994)

Downdating the Rank-Revealing URV Decomposition. - Haesun Park; Lars Eldén (SIAM J. Matrix Anal. Appl., 1995)

Fast computation of the principal singular vectors of Toeplitz matrices arising in exponential data modelling. - Lars Eldén; Eva Sjöström (Signal Process., 1996)

Approximating minimum norm solutions of rank-deficient least squares problems. - Achiya Dax; Lars Eldén (Numer. Linear Algebra Appl., 1998)

A Procrustes problem on the Stiefel manifold. - Lars Eldén; Haesun Park (Numerische Mathematik, 1999)

Wavelet and Fourier Methods for Solving the Sideways Heat Equation. - Lars Eldén; Fredrik Berntsson; Teresa Reginska (SIAM J. Sci. Comput., 2000)

Schur-Type Methods for Solving Least Squares Problems with Toeplitz Structure. - Haesun Park; Lars Eldén (SIAM J. Sci. Comput., 2000)

Adaptive Eigenvalue Computations Using Newton's Method on the Grassmann Manifold. - Eva Lundström; Lars Eldén (SIAM J. Matrix Anal. Appl., 2002)

Partial least-squares vs. Lanczos bidiagonalization - I: analysis of a projection method for multiple regression. - Lars Eldén (Comput. Stat. Data Anal., 2004)

The maximum likelihood estimate in reduced-rank regression. - Lars Eldén; Berkant Savas (Numer. Linear Algebra Appl., 2005)

Matrix methods in data mining and pattern recognition. - Lars Eldén (SIAM, 2007)

Non-negative Tensor Factorization Based on Alternating Large-scale Non-negativity-constrained Least Squares. - Hyunsoo Kim; Haesun Park; Lars Eldén (BIBE, 2007)

Handwritten digit classification using higher order singular value decomposition. - Berkant Savas; Lars Eldén (Pattern Recognit., 2007)

A Newton-Grassmann Method for Computing the Best Multilinear Rank-(r1, r2, r3) Approximation of a Tensor. - Lars Eldén; Berkant Savas (SIAM J. Matrix Anal. Appl., 2009)

Computing Word Senses by Semantic Mirroring and Spectral Graph Partitioning. - Martin Fagerlund; Magnus Merkel; Lars Eldén; Lars Ahrenberg (TextGraphs@ACL, 2010)

3rd Special issue on matrix computations and statistics. - Jesse L. Barlow; Lars Eldén; Paolo Foschi (Comput. Stat. Data Anal., 2010)

Data Mining, Networks and Dynamics (Dagstuhl Seminar 11451). - Lars Eldén; Andreas Frommer (Dagstuhl Reports, 2011)

Perturbation Theory and Optimality Conditions for the Best Multilinear Rank Approximation of a Tensor. - Lars Eldén; Berkant Savas (SIAM J. Matrix Anal. Appl., 2011)

Solving Ill-Posed Linear Systems with GMRES and a Singular Preconditioner. - Lars Eldén; Valeria Simoncini (SIAM J. Matrix Anal. Appl., 2012)

Computing Semantic Clusters by Semantic Mirroring and Spectral Graph Partitioning. - Lars Eldén; Magnus Merkel; Lars Ahrenberg; Martin Fagerlund (Math. Comput. Sci., 2013)

Best Kronecker Product Approximation of The Blurring Operator in Three Dimensional Image Restoration Problems. - Mansoor Rezghi; Seyed Mohammad Hosseini 002; Lars Eldén (SIAM J. Matrix Anal. Appl., 2014)

Solving an Ill-Posed Cauchy Problem for a Two-Dimensional Parabolic PDE with Variable Coefficients Using a Preconditioned GMRES Method. - Zohreh Ranjbar; Lars Eldén (SIAM J. Sci. Comput., 2014)

Solving bilinear tensor least squares problems and application to Hammerstein identification. - Lars Eldén; Salman Ahmadi-Asl (Numer. Linear Algebra Appl., 2019)

Spectral Partitioning of Large and Sparse Tensors using Low-Rank Tensor Approximation. - Lars Eldén; Maryam Dehghan (CoRR, 2020)

Analyzing Large and Sparse Tensor Data using Spectral Low-Rank Approximation. - Lars Eldén; Maryam Dehghan (CoRR, 2020)

A Krylov-Schur-like method for computing the best rank-(r1, r2, r3) approximation of large and sparse tensors. - Lars Eldén; Maryam Dehghan (Numer. Algorithms, 2022)

Spectral partitioning of large and sparse 3-tensors using low-rank tensor approximation. - Lars Eldén; Maryam Dehghan (Numer. Linear Algebra Appl., 2022)

Multiway Spectral Graph Partitioning: Cut Functions, Cheeger Inequalities, and a Simple Algorithm. - Lars Eldén (SIAM J. Matrix Anal. Appl., 2024)