50 citations · 268 across the 23 of their papers we have counts for
23 papers
Randomized algorithms for low-rank matrix approximation: Design, analysis, and applications
Joel A. Tropp, Robert J. Webber
This survey explores modern approaches for computing low-rank approximations of high-dimensional matrices by means of the randomized SVD, randomized subspace iteration, and randomi…
Mercury's chaotic secular evolution as a subdiffusive process
Dorian S. Abbot, Robert J. Webber, David M. Hernandez +2
Mercury's orbit can destabilize, generally resulting in a collision with either Venus or the Sun. Chaotic evolution can cause g1 to decrease to the approximately constant value of…
Robust, randomized preconditioning for kernel ridge regression
Mateo Díaz, Ethan N. Epperly, Zachary Frangella +2
We investigate preconditioned conjugate gradient methods for kernel ridge regression (KRR) problems with a moderate to large number of data points (). We dev…
Localized covariance estimation: A Bayesian perspective
Robert J. Webber, Matthias Morzfeld
A major problem in numerical weather prediction (NWP) is the estimation of high-dimensional covariance matrices from a small number of samples. Maximum likelihood estimators cannot…
XTrace: Making the most of every sample in stochastic trace estimation
Ethan N. Epperly, Joel A. Tropp, Robert J. Webber
The implicit trace estimation problem asks for an approximation of the trace of a square matrix, accessed via matrix-vector products (matvecs). This paper designs new randomized al…
Understanding and eliminating spurious modes in variational Monte Carlo using collective variables
Huan Zhang, Robert J. Webber, Michael Lindsey +2
The use of neural network parametrizations to represent the ground state in variational Monte Carlo (VMC) calculations has generated intense interest in recent years. However, as w…