43 citations · 72 across the 16 of their papers we have counts for
24 papers · 1 filter
Multi-scale Local Network Structure Critically Impacts Epidemic Spread and Interventions
Omar Eldaghar, Michael W. Mahoney, David F. Gleich
Network epidemic simulation holds the promise of enabling fine-grained understanding of epidemic behavior, beyond that which is possible with coarse-grained compartmental models. K…
Theoretical bounds on the network community profile from low-rank semi-definite programming
Yufan Huang, C. Seshadhri, David F. Gleich
We study a new connection between a technical measure called -conductance that arises in the study of Markov chains for sampling convex bodies and the network community profile…
fauci-email: a json digest of Anthony Fauci's released emails
Austin R. Benson, Nate Veldt, David F. Gleich
A collection of over 3000 pages of emails sent by Anthony Fauci and his staff were released in an effort to understand the United States government response to the COVID-19 pandemi…
Higher-order Network Analysis Takes Off, Fueled by Classical Ideas and New Data
Austin R. Benson, David F. Gleich, Desmond J. Higham
Higher-order network analysis uses the ideas of hypergraphs, simplicial complexes, multilinear and tensor algebra, and more, to study complex systems. These are by now well establi…
Strongly Local Hypergraph Diffusions for Clustering and Semi-supervised Learning
Meng Liu, Nate Veldt, Haoyu Song +2
Hypergraph-based machine learning methods are now widely recognized as important for modeling and using higher-order and multiway relationships between data objects. Local hypergra…
Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clustering
Meng Liu, David F. Gleich
Graph based semi-supervised learning is the problem of learning a labeling function for the graph nodes given a few example nodes, often called seeds, usually under the assumption…