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06/08/2023
Faster Approximation Algorithms for Parameterized Graph Clustering and Edge Labeling
Graph clustering is a fundamental task in network analysis where the goa...
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05/28/2023
Overlapping and Robust Edge-Colored Clustering in Hypergraphs
A recent trend in data mining has explored (hyper)graph clustering algor...
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04/02/2023
On the Optimal Recovery of Graph Signals
Learning a smooth graph signal from partially observed data is a well-st...
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03/20/2023
Seven open problems in applied combinatorics
We present and discuss seven different open problems in applied combinat...
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01/28/2023
Cut-matching Games for Generalized Hypergraph Ratio Cuts
Hypergraph clustering is a basic algorithmic primitive for analyzing com...
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09/10/2022
Growing a Random Maximal Independent Set Produces a 2-approximate Vertex Cover
This paper presents a fast and simple new 2-approximation algorithm for ...
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08/12/2022
Optimal LP Rounding and Fast Combinatorial Algorithms for Clustering Edge-Colored Hypergraphs
We study the approximability of a recently introduced framework for clus...
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11/20/2021
Faster Deterministic Approximation Algorithms for Correlation Clustering and Cluster Deletion
Correlation clustering is a framework for partitioning datasets based on...
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10/28/2021
Approximate Decomposable Submodular Function Minimization for Cardinality-Based Components
Minimizing a sum of simple submodular functions of limited support is a ...
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06/02/2021
The Generalized Mean Densest Subgraph Problem
Finding dense subgraphs of a large graph is a standard problem in graph ...
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03/22/2021
Higher-order Homophily is Combinatorially Impossible
Homophily is the seemingly ubiquitous tendency for people to connect wit...
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01/24/2021
Generative hypergraph clustering: from blockmodels to modularity
Hypergraphs are a natural modeling paradigm for a wide range of complex ...
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07/16/2020
Augmented Sparsifiers for Generalized Hypergraph Cuts
In recent years, hypergraph generalizations of many graph cut problems h...
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06/10/2020
Fair Clustering for Diverse and Experienced Groups
The ability for machine learning to exacerbate bias has led to many algo...
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02/21/2020
Parameterized Objectives and Algorithms for Clustering Bipartite Graphs and Hypergraphs
Graph clustering objective functions with tunable resolution parameters ...
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02/21/2020
Localized Flow-Based Clustering in Hypergraphs
Local graph clustering algorithms are designed to efficiently detect sma...
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01/09/2020
Hypergraph Cuts with General Splitting Functions
The minimum s-t cut problem in graphs is one of the most fundamental pro...
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10/22/2019
Hypergraph clustering with categorical edge labels
Graphs and networks are a standard model for describing data or systems ...
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10/14/2019
Graph Clustering in All Parameter Regimes
Resolution parameters in graph clustering represent a size and quality t...
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03/12/2019
Learning Resolution Parameters for Graph Clustering
Finding clusters of well-connected nodes in a graph is an extensively st...
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01/29/2019
A Parallel Projection Method for Metric Constrained Optimization
Many clustering applications in machine learning and data mining rely on...
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11/29/2018
Flow-Based Local Graph Clustering with Better Seed Set Inclusion
Flow-based methods for local graph clustering have received significant ...
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09/25/2018
Correlation Clustering Generalized
We present new results for LambdaCC and MotifCC, two recently introduced...
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06/05/2018
A Projection Method for Metric-Constrained Optimization
We outline a new approach for solving optimization problems which enforc...
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12/15/2017