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Mathematics

D-Index
37
Citations
4438
World Ranking
2549
National Ranking
1055

Research.com Recognitions

  • 2018 - Fellow of the American Association for the Advancement of Science (AAAS)
  • 2011 - SIAM Fellow For contributions to numerical linear algebra, perturbation theory, and applications.

Overview

Ilse C. F. Ipsen is affiliated with North Carolina State University in the United States. Their research spans a range of topics within computer science and mathematics, with a particular focus on matrix theory and algorithms, numerical methods, and statistical and numerical algorithms.

The main fields of study for Ipsen include:

  • Computer Science
  • Mathematics

Within these fields, Ipsen's work extends to several subfields, including:

  • Computational Theory and Mathematics
  • Statistics and Probability
  • Statistical and Nonlinear Physics
  • Molecular Biology
  • Applied Mathematics

The main research topics addressed in Ipsen's publications are:

  • Matrix Theory and Algorithms
  • Numerical Methods and Algorithms
  • Statistical and numerical algorithms
  • Sparse and Compressive Sensing Techniques
  • Probabilistic and Robust Engineering Design
  • Markov Chains and Monte Carlo Methods
  • Advanced Optimization Algorithms Research

Ipsen has published extensively, with frequent venues including:

  • arXiv (Cornell University)
  • SIAM Journal on Matrix Analysis and Applications
  • Numerische Mathematik
  • ePrints Soton (University of Southampton)
  • Frontiers in Genetics

Notable recent papers feature titles such as:

  • "Probabilistic Error Analysis for Inner Products" (2020), published in SIAM Journal on Matrix Analysis and Applications
  • "Precision-aware deterministic and probabilistic error bounds for floating point summation" (2023), published in Numerische Mathematik
  • "SEAGLE: A Scalable Exact Algorithm for Large-Scale Set-Based Gene-Environment Interaction Tests in Biobank Data" (2021), published in Frontiers in Genetics
  • "Monte Carlo Methods for Estimating the Diagonal of a Real Symmetric Matrix" (2023), published in SIAM Journal on Matrix Analysis and Applications
  • "Small Singular Values Can Increase in Lower Precision" (2024), published in SIAM Journal on Matrix Analysis and Applications

Frequent collaborators with Ipsen include:

  • Arvind K. Saibaba
  • Eric J. Hallman
  • Petros Drineas
  • T. Jocelyn
  • Christos Boutsikas

Over the course of their career, Ipsen has been recognized with awards such as:

  • Fellow of the American Association for the Advancement of Science (AAAS), awarded in 2018
  • SIAM Fellow, awarded in 2011 for contributions to numerical linear algebra, perturbation theory, and applications

Best Publications

  • THE IDEA BEHIND KRYLOV METHODS

    Ilse C. F. Ipsen;Carl D. Meyer

  • On Rank-Revealing Factorisations

    Shivkumar Chandrasekaran;Ilse C. F. Ipsen

  • Computing an Eigenvector with Inverse Iteration

    Ilse C. F. Ipsen

  • A Note on Preconditioning Nonsymmetric Matrices

    Ilse C. F. Ipsen

  • GMREs and the minimal polynomial

    Stephen L. Campbell;Ilse C. F. Ipsen;Carl Tim Kelley;Carl D. Meyer

  • How to Embed Trees in Hypercubes.

    Sandeep N. Bhatt;Ilse C. F. Ipsen

  • Relative perturbation techniques for singular value problems

    Stanley C. Eisenstat;Ilse C. F. Ipsen

  • PageRank Computation, with Special Attention to Dangling Nodes

    Ilse C. F. Ipsen;Teresa M. Selee

  • Ergodicity Coefficients Defined by Vector Norms

    Ilse C. F. Ipsen;Teresa M. Selee

  • Eigenvector Continuation with Subspace Learning.

    Dillon Frame;Dillon Frame;Rongzheng He;Rongzheng He;Ilse Ipsen;Daniel Lee

  • Relative perturbation results for matrix eigenvalues and singular values

    Ilse C. F. Ipsen

  • Systolic Networks for Orthogonal Decompositions

    Don E. Heller;Ilse C. F. Ipsen

  • The Angle Between Complementary Subspaces

    Ilse C. F. Ipsen;Carl D. Meyer

  • Numerical Matrix Analysis: Linear Systems and Least Squares

    Ilse C. F. Ipsen

  • Uniform Stability of Markov Chains

    Ilse C. F. Ipsen;Carl D. Meyer

  • Three Absolute Perturbation Bounds for Matrix Eigenvalues Imply Relative Bounds

    Stanley C. Eisenstat;Ilse C. F. Ipsen

  • Refined Perturbation Bounds for Eigenvalues of Hermitian and Non-Hermitian Matrices

    I. C. F. Ipsen;B. Nadler

  • Perturbation Bounds for Determinants and Characteristic Polynomials

    Ilse C. F. Ipsen;Rizwana Rehman

  • Convergence Analysis of a PageRank Updating Algorithm by Langville and Meyer

    Ilse C. F. Ipsen;Steve Kirkland

  • Complexity of dense-linear-system solution on a multiprocessor ring

    Ilse C.F. Ipsen;Youcef Saad;Martin H. Schultz

Frequent Co-Authors

Ralph C. Smith
Ralph C. Smith North Carolina State University
Petros Drineas
Petros Drineas Purdue University West Lafayette
Carl D. Meyer
Carl D. Meyer North Carolina State University
Carl Tim Kelley
Carl Tim Kelley North Carolina State University
Philipp Hennig
Philipp Hennig University of Tübingen
Malik Magdon-Ismail
Malik Magdon-Ismail Rensselaer Polytechnic Institute
Mark Girolami
Mark Girolami University of Cambridge
Timothy Sullivan
Timothy Sullivan University of Canterbury
Ioannis G. Kevrekidis
Ioannis G. Kevrekidis Johns Hopkins University
William Gropp
William Gropp University of Illinois at Urbana-Champaign

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