62 citations · 75 across the 7 of their papers we have counts for
16 papers
Approximate Decomposable Submodular Function Minimization for Cardinality-Based Components
Nate Veldt, Austin R. Benson, Jon Kleinberg
Minimizing a sum of simple submodular functions of limited support is a special case of general submodular function minimization that has seen numerous applications in machine lear…
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…
The Generalized Mean Densest Subgraph Problem
Nate Veldt, Austin R. Benson, Jon Kleinberg
Finding dense subgraphs of a large graph is a standard problem in graph mining that has been studied extensively both for its theoretical richness and its many practical applicatio…
Generative hypergraph clustering: from blockmodels to modularity
Philip S. Chodrow, Nate Veldt, Austin R. Benson
Hypergraphs are a natural modeling paradigm for a wide range of complex relational systems. A standard analysis task is to identify clusters of closely related or densely interconn…
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…
Hypergraph Clustering for Finding Diverse and Experienced Groups
Ilya Amburg, Nate Veldt, Austin R. Benson
When forming a team or group of individuals, we often seek a balance of expertise in a particular task while at the same time maintaining diversity of skills within each group. Her…