
Parameterized Objectives and Algorithms for Clustering Bipartite Graphs and Hypergraphs
Graph clustering objective functions with tunable resolution parameters ...
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Graph Clustering in All Parameter Regimes
Resolution parameters in graph clustering represent a size and quality t...
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Rigid Graph Alignment
Graph databases have been the subject of significant research and develo...
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Learning Resolution Parameters for Graph Clustering
Finding clusters of wellconnected nodes in a graph is an extensively st...
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A Parallel Projection Method for Metric Constrained Optimization
Many clustering applications in machine learning and data mining rely on...
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Correlation Clustering Generalized
We present new results for LambdaCC and MotifCC, two recently introduced...
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Low rank methods for multiple network alignment
Multiple network alignment is the problem of identifying similar and rel...
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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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Coinflipping, balldropping, and grasshopping for generating random graphs from matrices of edge probabilities
Common models for random graphs, such as ErdősRényi and Kronecker graph...
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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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Dynamic PageRank using Evolving Teleportation
The importance of nodes in a network constantly fluctuates based on chan...
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Moment based estimation of stochastic Kronecker graph parameters
Stochastic Kronecker graphs supply a parsimonious model for large sparse...
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David F. Gleich
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