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Lars Eldén

Professor emeritus of Scientific Computing
ORCID ID iconorcid.org/0000-0003-2281-856X



Recent papers

  • Solving an Ill-Posed Cauchy Problem for a Two-Dimensional Parabolic PDE with Variable Coefficients using a Preconditioned GMRES Method, SISC 2014  
    PDF   BIBTEX  
  • Computing Frechet Derivatives in Partial Least Squares Regresssion, LAA 2015  
    PDF   BIBTEX  
  • Computing Semantic Clusters by Semantic Mirroring and Spectral Graph Partitioning, Mathematics in Computer Science 2013  
    PDF   BIBTEX   Springer Link
  • Solving Ill-Posed Linear Systems with GMRES and a Singular Preconditioner, SIMAX 2012  
    PDF   BIBTEX  
  • Perturbation Theory and Optimality Conditions for the Best Multilinear Rank Approximation of a Tensor, SIMAX 2011,   PDF,    BIBTEX
  • Krylov-type methods for tensor computations I,  LAA 2012 
     BIBTEX

Editor-in-chief of BIT Numerical Mathematics

BIT at Springer
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Quotations about data analysis

"The traditional rationale within applied mathematics has been to solve or provide insight for equations which describe some part of the physical world. .... But there is a paradigm shift afoot. Mathematics is used to describe data, without the benefit of an interpolating equation or physical principle."
(J. Glimm, Bulletin of the American Mathematical Society, 47, Jan 2010, p. 127-136.)

"The analysis of large data sets to provide understanding, and ultimately knowledge, is one of the fundamental intellectual challenges of our time. It falls to practitioners of the mathematical sciences (mathematics, statistics, and computer science) to devise new methods for carrying out analysis tasks, as well as to construct new models or paradigms for thinking about data."
(Gunnar Carlsson and Robert Ghrist, SIAM News, April 2012).