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Center-based clustering has attracted significant research interest from both theory and practice. In many practical applications, input data often contain background knowledge that can be used to improve clustering results. In this work,…

Machine Learning · Computer Science 2025-06-13 Longkun Guo , Chaoqi Jia , Kewen Liao , Zhigang Lu , Minhui Xue

We study algorithms for estimating the size of maximum matching. This problem has been subject to extensive research. For $n$-vertex graphs, Bhattacharya, Kiss, and Saranurak [FOCS'23] (BKS) showed that an estimate that is within…

Data Structures and Algorithms · Computer Science 2024-06-14 Soheil Behnezhad , Mohammad Roghani , Aviad Rubinstein

The higher-order correlation clustering problem is an expressive model, and recently, local search heuristics have been proposed for several applications. Certifying optimality, however, is NP-hard and practically hampered already by the…

Discrete Mathematics · Computer Science 2023-04-03 David Stein , Silvia Di Gregorio , Bjoern Andres

The Bad Triangle Transversal (BTT) problem asks for the smallest set of edges that need to be removed from a given signed graph, so that the resulting graph does not have a bad triangle. Here, a bad triangle is a triangle with exactly one…

Data Structures and Algorithms · Computer Science 2026-05-28 Florian Adriaens , Nikolaj tatti

The problem of maximizing (or minimizing) the agreement between clusterings, subject to given marginals, can be formally posed under a common framework for several agreement measures. Until now, it was possible to find its solution only…

Machine Learning · Statistics 2020-01-22 José E. Chacón

In $k$-hypergraph matching, we are given a collection of sets of size at most $k$, each with an associated weight, and we seek a maximum-weight subcollection whose sets are pairwise disjoint. More generally, in $k$-hypergraph $b$-matching,…

Data Structures and Algorithms · Computer Science 2016-04-04 Ojas Parekh , David Pritchard

We present new results for LambdaCC and MotifCC, two recently introduced variants of the well-studied correlation clustering problem. Both variants are motivated by applications to network analysis and community detection, and have…

Computational Complexity · Computer Science 2018-09-26 David F. Gleich , Nate Veldt , Anthony Wirth

Betweenness Centrality (BC) is an important measure used widely in complex network analysis, such as social network, web page search, etc. Computing the exact BC values is highly time consuming. Currently the fastest exact BC determining…

Social and Information Networks · Computer Science 2017-12-21 Shiyu Ji , Zenghui Yan

The vertex cover problem is a fundamental and widely studied combinatorial optimization problem. It is known that its standard linear programming relaxation is integral for bipartite graphs and half-integral for general graphs. As a…

Data Structures and Algorithms · Computer Science 2023-07-28 Danish Kashaev , Guido Schäfer

For a given graph $G$ with positive integral cost and delay on edges, distinct vertices $s$ and $t$, cost bound $C\in Z^{+}$ and delay bound $D\in Z^{+}$, the $k$ bi-constraint path ($k$BCP) problem is to compute $k$ disjoint $st$-paths…

Data Structures and Algorithms · Computer Science 2013-04-04 Longkun Guo , Hong Shen , Kewen Liao

We explore Cluster Editing and its generalization Correlation Clustering with a new operation called permissive vertex splitting which addresses finding overlapping clusters in the face of uncertain information. We determine that both…

Data Structures and Algorithms · Computer Science 2024-08-30 Matthias Bentert , Alex Crane , Pål Grønås Drange , Felix Reidl , Blair D. Sullivan

Convex clustering has recently garnered increasing interest due to its attractive theoretical and computational properties, but its merits become limited in the face of high-dimensional data. In such settings, pairwise affinity terms that…

Methodology · Statistics 2021-04-02 Saptarshi Chakraborty , Jason Xu

For a positive integer $s$, an $s$-club in a graph $G$ is a set of vertices inducing a subgraph with diameter at most $s$. As generalizations of cliques, $s$-clubs offer a flexible model for real-world networks. This paper addresses the…

Computational Complexity · Computer Science 2026-04-21 Angelo Monti , Blerina Sinaimeri

The higher-order correlation clustering problem for a graph $G$ and costs associated with cliques of $G$ consists in finding a clustering of $G$ so as to minimize the sum of the costs of those cliques whose nodes all belong to the same…

Discrete Mathematics · Computer Science 2025-10-24 David Stein , Bjoern Andres , Silvia Di Gregorio

Motivated by an application from geodesy, we introduce a novel clustering problem which is a $k$-center (or k-diameter) problem with a side constraint. For the side constraint, we are given an undirected connectivity graph $G$ on the input…

Data Structures and Algorithms · Computer Science 2023-10-19 Lukas Drexler , Jan Eube , Kelin Luo , Dorian Reineccius , Heiko Röglin , Melanie Schmidt , Julian Wargalla

A number of attempts have been made to improve accuracy and/or scalability of the PC (Peter and Clark) algorithm, some well known (Buhlmann, et al., 2010; Kalisch and Buhlmann, 2007; 2008; Zhang, 2012, to give some examples). We add here…

Artificial Intelligence · Computer Science 2016-10-06 Joseph Ramsey

In this paper, we study correlation clustering under fairness constraints. Fair variants of $k$-median and $k$-center clustering have been studied recently, and approximation algorithms using a notion called fairlet decomposition have been…

Data Structures and Algorithms · Computer Science 2020-03-04 Sara Ahmadian , Alessandro Epasto , Ravi Kumar , Mohammad Mahdian

We study the Maximum Balanced Biclique (MBB) problem: Given a bipartite graph $G$ with $n$ vertices on each side, find a balanced biclique in $G$ with maximum size. We give a polynomial-time $\left(\frac{n}{\widetilde{\Omega}\left((\log…

Data Structures and Algorithms · Computer Science 2026-05-01 Pasin Manurangsi

Data de-duplication is the task of detecting multiple records that correspond to the same real-world entity in a database. In this work, we view de-duplication as a clustering problem where the goal is to put records corresponding to the…

Machine Learning · Computer Science 2020-05-27 Shrinu Kushagra , Shai Ben-David , Ihab Ilyas

We propose a \textit{purely combinatorial algorithm} for \mkvc{} in bipartite graphs, achieving approximation ratio~0.7. The only combinatorial algorithms currently known until now for this problem are the natural greedy algorithm, that…

Data Structures and Algorithms · Computer Science 2015-03-11 Vangelis Th. Paschos
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