
Higherorder clustering in networks
A fundamental property of complex networks is the tendency for edges to ...
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Motifs in Temporal Networks
Networks are a fundamental tool for modeling complex systems in a variet...
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Scalable methods for nonnegative matrix factorizations of nearseparable tallandskinny matrices
Numerous algorithms are used for nonnegative matrix factorization under ...
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Simplicial Closure and Higherorder Link Prediction
Networks provide a powerful formalism for modeling complex systems, by r...
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Random Walks on Simplicial Complexes and the normalized Hodge Laplacian
Modeling complex systems and data with graphs has been a mainstay of the...
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Three hypergraph eigenvector centralities
Eigenvector centrality is a standard network analysis tool for determini...
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Found Graph Data and Planted Vertex Covers
A typical way in which network data is recorded is to measure all the in...
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Corefringe link prediction
Data collection often involves the partial measurement of a larger syste...
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Computing tensor Zeigenvectors with dynamical systems
We present a new framework for computing Zeigenvectors of general tenso...
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Tools for higherorder network analysis
Networks are a fundamental model of complex systems throughout the scien...
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Modeling and Analysis of Tagging Networks in Stack Exchange Communities
Large QuestionandAnswer (Q&A) platforms support diverse knowledge cura...
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Planted Hitting Set Recovery in Hypergraphs
In various application areas, networked data is collected by measuring i...
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Graphbased SemiSupervised & Active Learning for Edge Flows
We present a graphbased semisupervised learning (SSL) method for learn...
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Neural Jump Stochastic Differential Equations
Many time series can be effectively modeled with a combination of contin...
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Incrementally Updated Spectral Embeddings
Several fundamental tasks in data science rely on computing an extremal ...
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Hypergraph clustering with categorical edge labels
Graphs and networks are a standard model for describing data or systems ...
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Retrieving Top Weighted Triangles in Graphs
Pattern counting in graphs is a fundamental primitive for many network a...
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Entrywise convergence of iterative methods for eigenproblems
Several problems in machine learning, statistics, and other fields rely ...
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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...
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Choice Set Optimization Under Discrete Choice Models of Group Decisions
The way that people make choices or exhibit preferences can be strongly ...
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Hypergraph Cuts with General Splitting Functions
The minimum st cut problem in graphs is one of the most fundamental pro...
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Localized FlowBased Clustering in Hypergraphs
Local graph clustering algorithms are designed to efficiently detect sma...
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Fair Clustering for Diverse and Experienced Groups
The ability for machine learning to exacerbate bias has led to many algo...
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Nonlinear HigherOrder Label Spreading
Label spreading is a general technique for semisupervised learning with...
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Expertise and Dynamics within Crowdsourced Musical Knowledge Curation: A Case Study of the Genius Platform
Many platforms collect crowdsourced information primarily from volunteer...
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A simple bipartite graph projection model for clustering in networks
Graph datasets are frequently constructed by a projection of a bipartite...
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Austin R. Benson
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