activity
20132022
most citedAn improved analysis and unified perspective on deterministic and randomized low rank matrix approximations

2 citations · 4 across the 4 of their papers we have counts for

collaborators

7 papers

cs.DC20221 cited

Tight Memory-Independent Parallel Matrix Multiplication Communication Lower Bounds

Hussam Al Daas, Grey Ballard, Laura Grigori +2

Communication lower bounds have long been established for matrix multiplication algorithms. However, most methods of asymptotic analysis have either ignored the constant factors or…

math.NA2022

A Directional Equispaced interpolation-based Fast Multipole Method for oscillatory kernels

Igor Chollet, Xavier Claeys, Pierre Fortin +1

Fast Multipole Methods (FMMs) based on the oscillatory Helmholtz kernel can reduce the cost of solving N-body problems arising from Boundary Integral Equations (BIEs) in acoustic o…

math.NA2020

Accelerating linear system solvers for time domain component separation of cosmic microwave background data

J. Papež, L. Grigori, R. Stompor

Component separation is one of the key stages of any modern, cosmic microwave background (CMB) data analysis pipeline. It is an inherently non-linear procedure and typically involv…

math.NA20192 cited

An improved analysis and unified perspective on deterministic and randomized low rank matrix approximations

James Demmel, Laura Grigori, Alexander Rusciano

We introduce a Generalized LU-Factorization (\textbf{GLU}) for low-rank matrix approximation. We relate this to past approaches and extensively analyze its approximation properties…

cs.LG2019

Parallel and Communication Avoiding Least Angle Regression

S. Das, J. Demmel, K. Fountoulakis +3

We are interested in parallelizing the Least Angle Regression (LARS) algorithm for fitting linear regression models to high-dimensional data. We consider two parallel and communica…

cs.DC2018

A 3D Parallel Algorithm for QR Decomposition

Grey Ballard, James Demmel, Laura Grigori +2

Interprocessor communication often dominates the runtime of large matrix computations. We present a parallel algorithm for computing QR decompositions whose bandwidth cost (communi…