Speaker Title
Michael S. Ackermann Leveraging Numerical Linear Algebra for Robust Learning of Optimal H2 models from time-domain data
Robin Armstrong Collect, Commit, Expand: an Efficient Strategy for Column Subset Selection on Extremely Wide Matrices
David S. Bindel Birkhoff Averages, Invariant Sets, and Adaptive Filtering
Erik G Boman Parallel Incomplete Factorization Preconditioners
Erin Carson The Stability of Split-Preconditioned FGMRES in Four Precisions
Fei Chen Convergence Behavior of GMRES on Tridiagonal Toeplitz Systems
Tyler Chen Preconditioning without a preconditioner: faster ridge-regression and Gaussian sampling with randomized block Krylov methods
Edmond Chow Online Machine Learning for Solving a Sequence of Linear Systems
Julianne Chung Efficient sample average approximation techniques for hyperparameter estimation in Bayesian inverse problems
Alice Cortinovis Fast Randomized Column Subset Selection Using Strong Rank-revealing QR
Anil Damle Rank-revealing QR factorizations: applications, algorithms, and theory
James Demmel On Minimizing Arithmetic and Communication Complexity of Jacobi’s Eigenvalue Method: Review and Beyond
Yijun Dong Toward Fast and Provable Data Selection under Low Intrinsic Dimension
Vladimir Druskin Nonlinear inverse scattering data transforms via casual transmutation matrices
Malena I. Español Variable Projection Methods for Regularized Separable Nonlinear Inverse Problems
Srinivas Eswar Bayesian Optimal Experiment Design via Column Subset Selection
Paola Ferrari Multigrid Methods for Solving Indefinite Problems in Port-Hamiltonian Systems
Isabella Furci Analysis on aggregation and block smoothers in multigrid methods for block structured linear systems
Nithin Govindarajan Towards Efficient Algorithms for Approximately Solving (Overdetermined) Systems of Polynomial Equations
Sophia Keip QCLAB: A MATLAB Toolbox for Quantum Numerical Linear Algebra
Misha E. Kilmer A Memory-efficient MM-GKS Variant for Large-scale Dynamic or Streaming Inverse Problems
Daniel Kressner Randomized solvers for joint eigenvalue problems
Hei Yin Lam Randomized low-rank Runge-Kutta methods
Rich Lehoucq Optimal accuracy for linear sets of equations with the graph Laplacian
Ren-Cang Li The NPDo Approach For Optimization On The Stiefel Manifold with Applications
Xiaobo Liu Mixed precision HODLR matrices
Robert Luce A MATLAB Toolbox for Toeplitz-Like Matrix Computations
Linjian Ma Efficient tensor network contraction algorithms
Roummel Marcia Inverse Eigenvalue Difference Problems Arising in Quantum Sensing
Karl Meerbergen Shift-and-invert Arnoldi for singular eigenvalue problems
Agnieszka Międlar On the Convergence of the CROP-Anderson Acceleration Method
Tim Mitchell Interpolation-Based Algorithms to Compute the H-infinity Norm of a Parametric System
Uria Mor Quasitubal Tensor Framework: Applications to Multiway Functional Data Analysis
James Nagy Inverse Problems, Kronecker Products and Mixed Precision Computations
Lucas Onisk Mixed Precision Iterative Refinement for Linear Inverse Problems
Carolin Penke Using a Blocked Adaptive Randomized Range Finder to Reduce Memory Requirements in Deep Learning Based on the Householder QR Decomposition
Vasilije Perović A hybrid method for computing a few singular triplets of very large sparse matrices
Anshul Prajapati Optimizing Rayleigh quotient with symmetric constraints and its application to eigenvalue backward errors of polynomial and rational eigenvalue problems
Leonardo Robol Preconditioned Low-Rank Riemannian Optimization for Symmetric Positive Definite Linear Matrix Equations
Michael Saunders Algorithm NCL for constrained optimization: Solving the linear systems within interior methods
Nian Shao Randomized small-block Lanczos for null space computations
Tianyi Shi Data-parallel adaptive tensor-train cross approximation
Kirk M. Soodhalter Filtration of Lanczos vectors in hybrid CG Tikhonov iteration
Martin Stoll Adaptive rational Krylov methods for exponential Runge-Kutta integrators on networks
Christine Tobler Quantum Computing in MATLAB
Alex Townsend The Quest for a Numerically Stable Multivariate Polynomial Rootfinder
Christopher Wang When does the randomized SVD actually compute an SVD? Randomized subspace approximation beyond singular value gaps
Liron Mor Yosef Efficient Classical-Quantum Algorithms for Matrix Encoding