64 citations · 195 across the 23 of their papers we have counts for
6 papers · 1 filter
Computing Steiner Trees using Graph Neural Networks
Reyan Ahmed, Md Asadullah Turja, Faryad Darabi Sahneh +3
Graph neural networks have been successful in many learning problems and real-world applications. A recent line of research explores the power of graph neural networks to solve com…
On Matrix Factorizations in Subspace Clustering
Reeshad Arian, Keaton Hamm
This article explores subspace clustering algorithms using CUR decompositions, and examines the effect of various hyperparameters in these algorithms on clustering performance on t…
Multi-level Weighted Additive Spanners
Reyan Ahmed, Greg Bodwin, Faryad Darabi Sahneh +3
Given a graph , a subgraph is an \emph{additive spanner} if $\dist_H(u,v) \le \dist_G(u,v) + β$ for all . A \emph{pairwise spanner} is a spanner for…
Mode-wise Tensor Decompositions: Multi-dimensional Generalizations of CUR Decompositions
HanQin Cai, Keaton Hamm, Longxiu Huang +1
Low rank tensor approximation is a fundamental tool in modern machine learning and data science. In this paper, we study the characterization, perturbation analysis, and an efficie…
On additive spanners in weighted graphs with local error
Reyan Ahmed, Greg Bodwin, Keaton Hamm +2
An \emph{additive spanner} of a graph is a subgraph which preserves distances up to an additive error. Additive spanners are well-studied in unweighted graphs but hav…
Robust CUR Decomposition: Theory and Imaging Applications
HanQin Cai, Keaton Hamm, Longxiu Huang +1
This paper considers the use of Robust PCA in a CUR decomposition framework and applications thereof. Our main algorithms produce a robust version of column-row factorizations of m…