93 citations · 388 across the 44 of their papers we have counts for
6 papers · 1 filter
CAST: Canonical Approximate Schur Tree for Approximate Cholesky on Graphs
Meher Chaitanya, Cameron Musco, Aristides Gionis
Graph-data workloads such as diffusion estimation, ranking, semi-supervised learning, and network optimization often solve many Laplacian or symmetric diagonally dominant M-matrix…
A Tight Analysis of Khatri-Rao Oblivious Subspace Embeddings
Lorenzo Beretta, Cameron Musco
We study random sketching matrices with Khatri-Rao structure. In particular, we consider the Khatri-Rao product (i.e., column-wise tensor product) $A_1\odot\cdots\odot A_d \in \mat…
Sublinear Time Eigenvector Approximation via Column Sampling
Rajarshi Bhattacharjee, Cameron Musco, Dominic Rutkowski
We study sublinear time sampling methods for approximating the outlying eigenvectors of large matrices. Our main result is an algorithm that uniformly samples just $\tilde{O}(\log…
Fast Length-Squared Sampling for Positive-Semidefinite Matrices
Rajarshi Bhattacharjee, Ethan N. Epperly, Cameron Musco +1
We describe a simple rejection-sampling-based algorithm to perform length-squared sampling on an positive-semidefinite (psd) matrix: that is, to sample a column with p…
Spectral density estimation for normal matrices
Cameron Musco, Christopher Musco, Rikhav Shah +2
The spectral density estimation problem asks for an algorithm that, given an matrix , outputs a probability measure that is a good approximation to the uniform distr…
Private Adaptive Covariance Estimation via Gaussian Graphical Models
Cecilia Ferrando, Miguel Fuentes, Brett Mullins +2
We propose PACE-GGM, a data-adaptive differentially private method for covariance estimation that concentrates its privacy budget on the most informative entries of the empirical c…