
Edge Proposal Sets for Link Prediction
Graphs are a common model for complex relational data such as social net...
read it

Graph Belief Propagation Networks
With the widespread availability of complex relational data, semisuper...
read it

The Generalized Mean Densest Subgraph Problem
Finding dense subgraphs of a large graph is a standard problem in graph ...
read it

Choice Set Confounding in Discrete Choice
Standard methods in preference learning involve estimating the parameter...
read it

A nonlinear diffusion method for semisupervised learning on hypergraphs
Hypergraphs are a common model for multiway relationships in data, and h...
read it

Higherorder Homophily is Combinatorially Impossible
Homophily is the seemingly ubiquitous tendency for people to connect wit...
read it

Random Graphs with Prescribed KCore Sequences: A New Null Model for Network Analysis
In the analysis of largescale network data, a fundamental operation is ...
read it

Generative hypergraph clustering: from blockmodels to modularity
Hypergraphs are a natural modeling paradigm for a wide range of complex ...
read it

A Unifying Generative Model for Graph Learning Algorithms: Label Propagation, Graph Convolutions, and Combinations
Semisupervised learning on graphs is a widely applicable problem in net...
read it

Overparametrized neural networks as underdetermined linear systems
We draw connections between simple neural networks and underdetermined ...
read it

Combining Label Propagation and Simple Models Outperforms Graph Neural Networks
Graph Neural Networks (GNNs) are the predominant technique for learning ...
read it

Learning Interpretable Feature Context Effects in Discrete Choice
The outcomes of elections, product sales, and the structure of social co...
read it

Communicationefficient distributed eigenspace estimation
Distributed computing is a standard way to scale up machine learning and...
read it

Augmented Sparsifiers for Generalized Hypergraph Cuts
In recent years, hypergraph generalizations of many graph cut problems h...
read it

A simple bipartite graph projection model for clustering in networks
Graph datasets are frequently constructed by a projection of a bipartite...
read it

Expertise and Dynamics within Crowdsourced Musical Knowledge Curation: A Case Study of the Genius Platform
Many platforms collect crowdsourced information primarily from volunteer...
read it

Fair Clustering for Diverse and Experienced Groups
The ability for machine learning to exacerbate bias has led to many algo...
read it

Nonlinear HigherOrder Label Spreading
Label spreading is a general technique for semisupervised learning with...
read it

Frozen Binomials on the Web: Word Ordering and Language Conventions in Online Text
There is inherent information captured in the order in which we write wo...
read it

Localized FlowBased Clustering in Hypergraphs
Local graph clustering algorithms are designed to efficiently detect sma...
read it

Entrywise convergence of iterative methods for eigenproblems
Several problems in machine learning, statistics, and other fields rely ...
read it

Choice Set Optimization Under Discrete Choice Models of Group Decisions
The way that people make choices or exhibit preferences can be strongly ...
read it

Hypergraph Cuts with General Splitting Functions
The minimum st cut problem in graphs is one of the most fundamental pro...
read it

Hypergraph clustering with categorical edge labels
Graphs and networks are a standard model for describing data or systems ...
read it

Retrieving Top Weighted Triangles in Graphs
Pattern counting in graphs is a fundamental primitive for many network a...
read it

Incrementally Updated Spectral Embeddings
Several fundamental tasks in data science rely on computing an extremal ...
read it

Neural Jump Stochastic Differential Equations
Many time series can be effectively modeled with a combination of contin...
read it

Graphbased SemiSupervised & Active Learning for Edge Flows
We present a graphbased semisupervised learning (SSL) method for learn...
read it

Planted Hitting Set Recovery in Hypergraphs
In various application areas, networked data is collected by measuring i...
read it

Modeling and Analysis of Tagging Networks in Stack Exchange Communities
Large QuestionandAnswer (Q&A) platforms support diverse knowledge cura...
read it

Corefringe link prediction
Data collection often involves the partial measurement of a larger syste...
read it

Three hypergraph eigenvector centralities
Eigenvector centrality is a standard network analysis tool for determini...
read it

Random Walks on Simplicial Complexes and the normalized Hodge Laplacian
Modeling complex systems and data with graphs has been a mainstay of the...
read it

Found Graph Data and Planted Vertex Covers
A typical way in which network data is recorded is to measure all the in...
read it

Computing tensor Zeigenvectors with dynamical systems
We present a new framework for computing Zeigenvectors of general tenso...
read it

Simplicial Closure and Higherorder Link Prediction
Networks provide a powerful formalism for modeling complex systems, by r...
read it

Tools for higherorder network analysis
Networks are a fundamental model of complex systems throughout the scien...
read it

Higherorder clustering in networks
A fundamental property of complex networks is the tendency for edges to ...
read it

Motifs in Temporal Networks
Networks are a fundamental tool for modeling complex systems in a variet...
read it

Scalable methods for nonnegative matrix factorizations of nearseparable tallandskinny matrices
Numerous algorithms are used for nonnegative matrix factorization under ...
read it
Austin R. Benson
is this you? claim profile