papers

Publications (93)

cs.LG2023

Latent Random Steps as Relaxations of Max-Cut, Min-Cut, and More

Sudhanshu Chanpuriya, Cameron Musco

Algorithms for node clustering typically focus on finding homophilous structure in graphs. That is, they find sets of similar nodes with many edges within, rather than across, the…

cs.LG2021

On the Power of Edge Independent Graph Models

Sudhanshu Chanpuriya, Cameron Musco, Konstantinos Sotiropoulos +1

Why do many modern neural-network-based graph generative models fail to reproduce typical real-world network characteristics, such as high triangle density? In this work we study t…

cs.LG2020

Subspace Embeddings Under Nonlinear Transformations

Aarshvi Gajjar, Cameron Musco

We consider low-distortion embeddings for subspaces under \emph{entrywise nonlinear transformations}. In particular we seek embeddings that preserve the norm of all vectors in a sp…

cs.DS2022

Fast Regression for Structured Inputs

Raphael A. Meyer, Cameron Musco, Christopher Musco +2

We study the regression problem, which requires finding that minimizes for a matrix $\mathbf{A}\in\mat…

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.SI2017

Minimizing Polarization and Disagreement in Social Networks

Cameron Musco, Christopher Musco, Charalampos E. Tsourakakis

The rise of social media and online social networks has been a disruptive force in society. Opinions are increasingly shaped by interactions on online social media, and social phen…