Cover Image

Adaptive randomized pivoting and volume sampling

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Epperly, Ethan N.
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Data Structures and Algorithms Numerical Analysis Computation 65F55, 68W20
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Make the most of what you have: Resource-efficient randomized algorithms for matrix computations
by: Epperly, Ethan N.
Published: (2025)

Faster Linear Algebra Algorithms with Structured Random Matrices
by: Camaño, Chris, et al.
Published: (2025)

Sharp analysis of sketched least squares and randomized low-rank approximation
by: Epperly, Ethan N., et al.
Published: (2026)

Quasi-optimal hierarchically semi-separable matrix approximation
by: Amsel, Noah, et al.
Published: (2025)

Efficient error and variance estimation for randomized matrix computations
by: Epperly, Ethan N., et al.
Published: (2022)

Robust, randomized preconditioning for kernel ridge regression
by: Díaz, Mateo, et al.
Published: (2023)

Adaptive randomized pivoting for column subset selection, DEIM, and low-rank approximation
by: Cortinovis, Alice, et al.
Published: (2024)

Linear-Scaling Tensor Train Sketching
by: Cazeaux, Paul, et al.
Published: (2026)

Algorithm-agnostic low-rank approximation of operator monotone matrix functions
by: Persson, David, et al.
Published: (2023)

Embrace rejection: Kernel matrix approximation by accelerated randomly pivoted Cholesky
by: Epperly, Ethan N., et al.
Published: (2024)

BOLT: Block-Orthonormal Lanczos for Trace estimation of matrix functions
by: Yeon, Kingsley, et al.
Published: (2025)

Fast and forward stable randomized algorithms for linear least-squares problems
by: Epperly, Ethan N.
Published: (2023)

A Randomized Algorithm for Preconditioner Selection
by: DiPaolo, Conner, et al.
Published: (2019)

Fast randomized least-squares solvers can be just as accurate and stable as classical direct solvers
by: Epperly, Ethan N., et al.
Published: (2024)

Randomly pivoted Cholesky: Practical approximation of a kernel matrix with few entry evaluations
by: Chen, Yifan, et al.
Published: (2022)

Randomized coupled decompositions
by: Begovic, Erna, et al.
Published: (2024)

Row-aware Randomized SVD with applications
by: Palitta, Davide, et al.
Published: (2024)

Does block size matter in randomized block Krylov low-rank approximation?
by: Chen, Tyler, et al.
Published: (2025)

Fast, High-Accuracy, Randomized Nullspace Computations for Tall Matrices
by: Epperly, Ethan N., et al.
Published: (2026)

XTrace: Making the most of every sample in stochastic trace estimation
by: Epperly, Ethan N., et al.
Published: (2023)

Randomized block-Krylov subspace methods for low-rank approximation of matrix functions
by: Persson, David, et al.
Published: (2025)

Oblivious Subspace Injection Is Not Enough for Relative Error
by: Townsend, Alex, et al.
Published: (2026)

Numerical Instabilities in the Kaczmarz Method and Stabilization by Iterative Refinement
by: Dereziński, Michał, et al.
Published: (2026)

Fast Rank Adaptive CUR via a Recycled Small Sketch
by: Pritchard, Nathaniel, et al.
Published: (2025)

Undercomplete Decomposition of Symmetric Tensors in Linear Time, and Smoothed Analysis of the Condition Number
by: Koiran, Pascal, et al.
Published: (2024)

Fast randomized numerical rank estimation for numerically low-rank matrices
by: Meier, Maike, et al.
Published: (2021)

Randomized batch-sampling Kaczmarz methods for solving linear systems
by: Xie, Dong-Yue, et al.
Published: (2025)

On the fast convergence of minibatch heavy ball momentum
by: Bollapragada, Raghu, et al.
Published: (2022)

Fast and Accurate Interpolative Decompositions for General, Sparse, and Structured Tensors
by: Zhang, Yifan, et al.
Published: (2025)

Randomized algorithms for streaming low-rank approximation in tree tensor network format
by: Bucci, Alberto, et al.
Published: (2024)

A sequential multilinear Nyström algorithm for streaming low-rank approximation of tensors in Tucker format
by: Bucci, Alberto, et al.
Published: (2024)

Low-rank approximation of parameter-dependent matrices via CUR decomposition
by: Park, Taejun, et al.
Published: (2024)

Improving Sketching Algorithms for Low-Rank Matrix Approximation via Sketch-Power Iterations
by: Chang, Chao, et al.
Published: (2026)

Efficient error estimators for Generalized Nyström
by: Lazzarino, Lorenzo, et al.
Published: (2026)

Randomized Large-Scale Quaternion Matrix Approximation: Practical Rangefinders and One-Pass Algorithm
by: Chang, Chao, et al.
Published: (2024)

Superfast direct inversion of the nonuniform discrete Fourier transform via hierarchically semi-separable least squares
by: Wilber, Heather, et al.
Published: (2024)

Strongly Sublinear Algorithms for Testing Pattern Freeness
by: Newman, Ilan, et al.
Published: (2021)

Sequential Least-Squares Estimators with Fast Randomized Sketching for Linear Statistical Models
by: Chen, Guan-Yu, et al.
Published: (2025)

On a randomized small-block Lanczos method for large-scale null space computations
by: Kressner, Daniel, et al.
Published: (2024)

Hybrid hierarchical matrices with adaptive mixed precision storage
by: Khan, Ritesh, et al.
Published: (2026)