activity
20162022
most citedFaster Spectral Sparsification in Dynamic Streams

4 citations · 14 across the 8 of their papers we have counts for

collaborators

12 papers

cs.DS2021

Faster Kernel Matrix Algebra via Density Estimation

Arturs Backurs, Piotr Indyk, Cameron Musco +1

We study fast algorithms for computing fundamental properties of a positive semidefinite kernel matrix corresponding to points $x_1,\ldots,x_n \…

cs.LG2020

Estimation of Shortest Path Covariance Matrices

Raj Kumar Maity, Cameron Musco

We study the sample complexity of estimating the covariance matrix of a distribution over given independent sample…

cs.DS20204 cited

Projection-Cost-Preserving Sketches: Proof Strategies and Constructions

Cameron Musco, Christopher Musco

In this note we illustrate how common matrix approximation methods, such as random projection and random sampling, yield projection-cost-preserving sketches, as introduced in [FSS1…

cs.DS2019

Low-Rank Toeplitz Matrix Estimation via Random Ultra-Sparse Rulers

Hannah Lawrence, Jerry Li, Cameron Musco +1

We study how to estimate a nearly low-rank Toeplitz covariance matrix from compressed measurements. Recent work of Qiao and Pal addresses this problem by combining sparse ruler…

eess.SP2019

Sample Efficient Toeplitz Covariance Estimation

Yonina C. Eldar, Jerry Li, Cameron Musco +1

We study the sample complexity of estimating the covariance matrix of a distribution over -dimensional vectors, under the assumption that is Toeplitz. This…

cs.DS20194 cited

Faster Spectral Sparsification in Dynamic Streams

Michael Kapralov, Aida Mousavifar, Cameron Musco +2

Graph sketching has emerged as a powerful technique for processing massive graphs that change over time (i.e., are presented as a dynamic stream of edge updates) over the past few…