Direct QR factorizations for tall-and-skinny matrices in MapReduce architectures. - Austin R. Benson; David F. Gleich; James Demmel (IEEE BigData, 2013)

Learning multifractal structure in large networks. - Austin R. Benson; Carlos Riquelme; Sven Schmit (KDD, 2014)

Scalable Methods for Nonnegative Matrix Factorizations of Near-separable Tall-and-skinny Matrices. - Austin R. Benson; Jason D. Lee; Bartek Rajwa; David F. Gleich (NIPS, 2014)

A Parallel Directional Fast Multipole Method. - Austin R. Benson; Jack Poulson; Kenneth Tran; Björn Engquist; Lexing Ying (SIAM J. Sci. Comput., 2014)

A framework for practical parallel fast matrix multiplication. - Austin R. Benson; Grey Ballard (PPoPP, 2015)

Tensor Spectral Clustering for Partitioning Higher-order Network Structures. - Austin R. Benson; David F. Gleich; Jure Leskovec (SDM, 2015)

Improving the numerical stability of fast matrix multiplication algorithms. - Grey Ballard; Austin R. Benson; Alex Druinsky; Benjamin Lipshitz; Oded Schwartz (CoRR, 2015)

Silent error detection in numerical time-stepping schemes. - Austin R. Benson; Sven Schmit; Robert Schreiber (Int. J. High Perform. Comput. Appl., 2015)

General Tensor Spectral Co-clustering for Higher-Order Data. - Tao Wu 019; Austin R. Benson; David F. Gleich (NIPS, 2016)

Modeling User Consumption Sequences. - Austin R. Benson; Ravi Kumar 001; Andrew Tomkins (WWW, 2016)

On the Relevance of Irrelevant Alternatives. - Austin R. Benson; Ravi Kumar 001; Andrew Tomkins (WWW, 2016)

Higher-order organization of complex networks. - Austin R. Benson; David F. Gleich; Jure Leskovec (CoRR, 2016)

Improving the Numerical Stability of Fast Matrix Multiplication. - Grey Ballard; Austin R. Benson; Alex Druinsky; Benjamin Lipshitz; Oded Schwartz (SIAM J. Matrix Anal. Appl., 2016)

Local Higher-Order Graph Clustering. - Hao Yin; Austin R. Benson; Jure Leskovec; David F. Gleich (KDD, 2017)

Motifs in Temporal Networks. - Ashwin Paranjape; Austin R. Benson; Jure Leskovec (WSDM, 2017)

Higher-order clustering in networks. - Hao Yin; Austin R. Benson; Jure Leskovec (CoRR, 2017)

The Spacey Random Walk: A Stochastic Process for Higher-Order Data. - Austin R. Benson; David F. Gleich; Lek-Heng Lim (SIAM Rev., 2017)

Sequences of Sets. - Austin R. Benson; Ravi Kumar 001; Andrew Tomkins (KDD, 2018)

Found Graph Data and Planted Vertex Covers. - Austin R. Benson; Jon M. Kleinberg (NeurIPS, 2018)

A Discrete Choice Model for Subset Selection. - Austin R. Benson; Ravi Kumar 001; Andrew Tomkins (WSDM, 2018)

Tools for higher-order network analysis. - Austin R. Benson (CoRR, 2018)

Random Walks on Simplicial Complexes and the normalized Hodge Laplacian. - Michael T. Schaub; Austin R. Benson; Paul Horn; Gabor Lippner; Ali Jadbabaie (CoRR, 2018)

Detecting Core-Periphery Structure in Spatial Networks. - Junteng Jia; Austin R. Benson (CoRR, 2018)

A sampling framework for counting temporal motifs. - Paul Liu 001; Austin R. Benson; Moses Charikar (CoRR, 2018)

Core-fringe link prediction. - Austin R. Benson; Jon M. Kleinberg (CoRR, 2018)

Simplicial closure and higher-order link prediction. - Austin R. Benson; Rediet Abebe; Michael T. Schaub; Ali Jadbabaie; Jon M. Kleinberg (Proc. Natl. Acad. Sci. USA, 2018)

Pairwise link prediction. - Huda Nassar; Austin R. Benson; David F. Gleich (ASONAM, 2019)

Network Density of States. - Kun Dong; Austin R. Benson; David Bindel (KDD, 2019)

Graph-based Semi-Supervised & Active Learning for Edge Flows. - Junteng Jia; Michael T. Schaub; Santiago Segarra; Austin R. Benson (KDD, 2019)

Neural Jump Stochastic Differential Equations. - Junteng Jia; Austin R. Benson (NeurIPS, 2019)

Random Spatial Network Models for Core-Periphery Structure. - Junteng Jia; Austin R. Benson (WSDM, 2019)

Sampling Methods for Counting Temporal Motifs. - Paul Liu 001; Austin R. Benson; Moses Charikar (WSDM, 2019)

The Local Closure Coefficient: A New Perspective On Network Clustering. - Hao Yin; Austin R. Benson; Jure Leskovec (WSDM, 2019)

Link Prediction in Networks with Core-Fringe Data. - Austin R. Benson; Jon M. Kleinberg (WWW, 2019)

Choosing to Grow a Graph: Modeling Network Formation as Discrete Choice. - Jan Overgoor; Austin R. Benson; Johan Ugander (WWW, 2019)

Modeling and Analysis of Tagging Networks in Stack Exchange Communities. - Xiang Fu 005; Shangdi Yu; Austin R. Benson (CoRR, 2019)

Planted Hitting Set Recovery in Hypergraphs. - Ilya Amburg; Jon M. Kleinberg; Austin R. Benson (CoRR, 2019)

Incrementally Updated Spectral Embeddings. - Vasileios Charisopoulos; Austin R. Benson; Anil Damle (CoRR, 2019)

Hypergraph clustering with categorical edge labels. - Ilya Amburg; Nate Veldt; Austin R. Benson (CoRR, 2019)

Computing Tensor Z-Eigenvectors with Dynamical Systems. - Austin R. Benson; David F. Gleich (SIAM J. Matrix Anal. Appl., 2019)

Three Hypergraph Eigenvector Centralities. - Austin R. Benson (SIAM J. Math. Data Sci., 2019)

Choice Set Optimization Under Discrete Choice Models of Group Decisions. - Kiran Tomlinson; Austin R. Benson (ICML, 2020)

Residual Correlation in Graph Neural Network Regression. - Junteng Jia; Austin R. Benson (KDD, 2020)

Minimizing Localized Ratio Cut Objectives in Hypergraphs. - Nate Veldt; Austin R. Benson; Jon M. Kleinberg (KDD, 2020)

Entrywise convergence of iterative methods for eigenproblems. - Vasileios Charisopoulos; Austin R. Benson; Anil Damle (NeurIPS, 2020)

Better Set Representations For Relational Reasoning. - Qian Huang; Horace He; Abhay Singh; Yan Zhang; Ser-Nam Lim; Austin R. Benson (NeurIPS, 2020)

Retrieving Top Weighted Triangles in Graphs. - Raunak Kumar; Paul Liu 001; Moses Charikar; Austin R. Benson (WSDM, 2020)

Clustering in graphs and hypergraphs with categorical edge labels. - Ilya Amburg; Nate Veldt; Austin R. Benson (WWW, 2020)

Frozen Binomials on the Web: Word Ordering and Language Conventions in Online Text. - Katherine Van Koevering; Austin R. Benson; Jon M. Kleinberg (WWW, 2020)

Using Cliques with Higher-order Spectral Embeddings Improves Graph Visualizations. - Huda Nassar; Caitlin Kennedy; Shweta Jain 003; Austin R. Benson; David F. Gleich (WWW, 2020)

Outcome Correlation in Graph Neural Network Regression. - Junteng Jia; Austin R. Benson (CoRR, 2020)

Localized Flow-Based Clustering in Hypergraphs. - Nate Veldt; Austin R. Benson; Jon M. Kleinberg (CoRR, 2020)

Set-Structured Latent Representations. - Qian Huang; Horace He; Abhay Singh; Yan Zhang; Ser-Nam Lim; Austin R. Benson (CoRR, 2020)

Fair Clustering for Diverse and Experienced Groups. - Ilya Amburg; Nate Veldt; Austin R. Benson (CoRR, 2020)

A simple bipartite graph projection model for clustering in networks. - Austin R. Benson; Paul Liu 001; Hao Yin (CoRR, 2020)

Over-parametrized neural networks as under-determined linear systems. - Austin R. Benson; Anil Damle; Alex Townsend (CoRR, 2020)

Measuring directed triadic closure with closure coefficients. - Hao Yin; Austin R. Benson; Johan Ugander (Netw. Sci., 2020)

Random Walks on Simplicial Complexes and the Normalized Hodge 1-Laplacian. - Michael T. Schaub; Austin R. Benson; Paul Horn; Gabor Lippner; Ali Jadbabaie (SIAM Rev., 2020)

Network Interpolation. - Thomas Reeves; Anil Damle; Austin R. Benson (SIAM J. Math. Data Sci., 2020)

Neighborhood and PageRank methods for pairwise link prediction. - Huda Nassar; Austin R. Benson; David F. Gleich (Soc. Netw. Anal. Min., 2020)

Combining Label Propagation and Simple Models out-performs Graph Neural Networks. - Qian Huang; Horace He; Abhay Singh; Ser-Nam Lim; Austin R. Benson (ICLR, 2021)

Expertise and Dynamics within Crowdsourced Musical Knowledge Curation: A Case Study of the Genius Platform. - Derek Lim; Austin R. Benson (ICWSM, 2021)

Learning Interpretable Feature Context Effects in Discrete Choice. - Kiran Tomlinson; Austin R. Benson (KDD, 2021)

Choice Set Confounding in Discrete Choice. - Kiran Tomlinson; Johan Ugander; Austin R. Benson (KDD, 2021)

The Generalized Mean Densest Subgraph Problem. - Nate Veldt; Austin R. Benson; Jon M. Kleinberg (KDD, 2021)

Approximate Decomposable Submodular Function Minimization for Cardinality-Based Components. - Nate Veldt; Austin R. Benson; Jon M. Kleinberg (NeurIPS, 2021)

Random Graphs with Prescribed K-Core Sequences: A New Null Model for Network Analysis. - Katherine Van Koevering; Austin R. Benson; Jon M. Kleinberg (WWW, 2021)

Nonlinear Higher-Order Label Spreading. - Francesco Tudisco; Austin R. Benson; Konstantin Prokopchik (WWW, 2021)

Modelling and analysis of tagging networks in Stack Exchange communities. - Xiang Fu 005; Shangdi Yu; Austin R. Benson (J. Complex Networks, 2021)

Generative hypergraph clustering: from blockmodels to modularity. - Philip S. Chodrow; Nate Veldt; Austin R. Benson (CoRR, 2021)

Higher-order Network Analysis Takes Off, Fueled by Classical Ideas and New Data. - Austin R. Benson; David F. Gleich; Desmond J. Higham (CoRR, 2021)

Higher-order Homophily is Combinatorially Impossible. - Nate Veldt; Austin R. Benson; Jon M. Kleinberg (CoRR, 2021)

A nonlinear diffusion method for semi-supervised learning on hypergraphs. - Francesco Tudisco; Konstantin Prokopchik; Austin R. Benson (CoRR, 2021)

Graph Belief Propagation Networks. - Junteng Jia; Cenk Baykal; Vamsi K. Potluru; Austin R. Benson (CoRR, 2021)

Edge Proposal Sets for Link Prediction. - Abhay Singh; Qian Huang; Sijia Linda Huang; Omkar Bhalerao; Horace He; Ser-Nam Lim; Austin R. Benson (CoRR, 2021)

Higher Order Information Identifies Tie Strength. - Arnab Sarker; Jean-Baptiste Seby; Austin R. Benson; Ali Jadbabaie (CoRR, 2021)

Communication-Efficient Distributed Eigenspace Estimation. - Vasileios Charisopoulos; Austin R. Benson; Anil Damle (SIAM J. Math. Data Sci., 2021)

Nonlinear Feature Diffusion on Hypergraphs. - Konstantin Prokopchik; Austin R. Benson; Francesco Tudisco (ICML, 2022)

Fauci-Email: A JSON Digest of Anthony Fauci's Released Emails. - Austin R. Benson; Nate Veldt; David F. Gleich (ICWSM, 2022)

Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference Perspective. - Rongzhe Wei; Haoteng Yin; Junteng Jia; Austin R. Benson; Pan Li 005 (NeurIPS, 2022)

Diverse and Experienced Group Discovery via Hypergraph Clustering. - Ilya Amburg; Nate Veldt; Austin R. Benson (SDM, 2022)

Hypergraph patterns and collaboration structure. - Jonas L. Juul; Austin R. Benson; Jon M. Kleinberg (CoRR, 2022)

Hypergraph Cuts with General Splitting Functions. - Nate Veldt; Austin R. Benson; Jon M. Kleinberg (SIAM Rev., 2022)

A Unifying Generative Model for Graph Learning Algorithms: Label Propagation, Graph Convolutions, and Combinations. - Junteng Jia; Austin R. Benson (SIAM J. Math. Data Sci., 2022)

Combinatorial Measures of Higher-order Homophily for Group Interaction Datasets. - Nate Veldt; Austin R. Benson; Jon M. Kleinberg (Zenodo, 2022)

Augmented Sparsifiers for Generalized Hypergraph Cuts. - Nate Veldt; Austin R. Benson; Jon M. Kleinberg (J. Mach. Learn. Res., 2023)

Graph-based methods for discrete choice. - Kiran Tomlinson; Austin R. Benson (Netw. Sci., 2024)