ANCHP

Chair of Numerical Algorithms and High-Performance Computing

Teaching in Fall 2024:

MATH-251(a) Numerical analysis
MATH-403 Randomized matrix computations

Recent preprints

arXiv:2409.06384 Hei Yin Lam, Gianluca Ceruti, Daniel Kressner: Randomized low-rank Runge-Kutta methods

arXiv:2409.00500 Haoze He, Daniel Kressner, Bor Plestenjak: Randomized methods for computing joint eigenvalues, with applications to multiparameter eigenvalue problems and root finding

arXiv:2408.16416 Ivan Bioli, Daniel Kressner, Leonardo Robol: Preconditioned low-rank Riemannian optimization for symmetric positive definite linear matrix equations

arXiv:2407.04634 Daniel Kressner, Nian Shao: A randomized small-block Lanczos method for large-scale null space computations

arXiv:2405.18399 Haoze He, Daniel Kressner: A simple, randomized algorithm for diagonalizing normal matrices

arXiv:2405.11962 Zvonimir Bujanović, Luka Grubišić, Daniel Kressner, Hei Yin Lam: Subspace embedding with random Khatri-Rao products and its application to eigensolvers

arXiv:2405.09952 Gianluca Ceruti, Daniel Kressner, Dominik Sulz: Low-rank tree tensor network operators for long-range pairwise interactions

arXiv:2404.00960 David Persson, Nicolas Boullé, Daniel Kressner: Randomized Nyström approximation of non-negative self-adjoint operators

arXiv:2402.17369 Angelo A. Casulli, Daniel Kressner, Leonardo Robol: Computing functions of symmetric hierarchically semiseparable matrices

arXiv:2402.16557 Haoze He, Daniel Kressner: A randomized algorithm for simultaneously diagonalizing symmetric matrices by congruence

arXiv:2401.11786 Nian Shao, Wenbin Chen, Zhaojun Bai: EPIC: a provable accelerated eigensolver based on preconditioning and implicit convexity

arXiv:2311.14023 David Persson, Raphael A. Meyer, Christopher Musco: Algorithm-agnostic low-rank approximation of operator monotone matrix functions

arXiv:2309.06125 Axel Séguin, Gianluca Ceruti, Daniel Kressner: From low-rank retractions to dynamical low-rank approximation and back

arXiv:2309.05143 Nian Shao, Wenbin Chen: Riemannian acceleration with preconditioning for symmetric eigenvalue problems

arXiv:2309.02156 Margherita Guido, Daniel Kressner, Paolo Ricci: Subspace acceleration for a sequence of linear systems and application to plasma simulation

arXiv:2306.01485 Dayana Savostianova, Emanuele Zangrando, Gianluca Ceruti, Francesco Tudisco: Robust low-rank training via approximate orthonormal constraints