10 Most Highly Cited Articles From SIMAX Since 2019

SIAM Journal on Matrix Analysis and Applications (SIMAX) publishes research papers on matrix and tensor theory, analysis, applications, and computation that are of interest to the applied and numerical linear algebra communities. Applications include such areas as signal processing, systems and control theory, statistics, Markov chains, mathematical biology, graph theory, and data science. 

Click below to read the 10 most highly cited articles from SIMAX since 2019:

• Conditioning of Partial Nonuniform Fourier Matrices with Clustered Nodes (Dmitry Batenkov, Laurent Demanet, Gil Goldman, and Yosef Yomdin)
• Block Krylov Subspace Methods for Functions of Matrices II: Modified Block FOM (Andreas Frommer, Kathryn Lund, and Daniel B. Szyld)
• Optimal Robustness of Port-Hamiltonian Systems (Volker Mehrmann, and Paul M. Van Dooren)
• Stochastic Reformulations of Linear Systems: Algorithms and Convergence Theory (Peter Richtárik, and Martin Takáč)
• Quotient Geometry with Simple Geodesics for the Manifold of Fixed-Rank Positive-Semidefinite Matrices (Estelle Massart ,and P.-A. Absil)
• Solving the Three-Dimensional High-frequency Helmholtz Equation Using Contour Integration and Polynomial Preconditioning (Xiao Liu, Yuanzhe Xi, Yousef Saad, and Maarten V. de Hoop)
• An Algebraic Sparsified Nested Dissection Algorithm Using Low-Rank Approximations (Léopold Cambier, Chao Chen, Erik G. Boman, Sivasankaran Rajamanickam, Raymond S. Tuminaro, and Eric Darve)
• The AZ Algorithm for Least Squares Systems with a Known Incomplete Generalized Inverse (Vincent Coppé,Daan Huybrechs, Roel Matthysen, and Marcus Webb)
• A Multigrid Method for Nonlocal Problems: Non--Diagonally Dominant or Toeplitz-Plus-Tridiagonal Systems (Minghua Chen, Sven-Erik Ekström, and Stefano Serra-Capizzano)
• Riemannian Modified Polak--Ribière--Polyak Conjugate Gradient Order Reduced Model by Tensor Techniques (Yao-Lin Jiang, and Kang-Li Xu)

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