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Convex clustering is an attractive clustering algorithm with favorable properties such as efficiency and optimality owing to its convex formulation. It is thought to generalize both k-means clustering and agglomerative clustering. However,…

Machine Learning · Statistics 2021-05-19 Canh Hao Nguyen , Hiroshi Mamitsuka

We give a polynomial-time algorithm that finds a planted clique of size $k \ge \sqrt{n \log n}$ in the semirandom model, improving the state-of-the-art $\sqrt{n} (\log n)^2$ bound. This $\textit{semirandom planted clique problem}$ concerns…

Data Structures and Algorithms · Computer Science 2025-06-24 Venkatesan Guruswami , Hsin-Po Wang

Recently, many studies have been devoted to finding diverse solutions in classical combinatorial problems, such as Vertex Cover (Baste et al., IJCAI'20), Matching (Fomin et al., ISAAC'20) and Spanning Tree (Hanaka et al., AAAI'21). We…

Data Structures and Algorithms · Computer Science 2024-09-19 Mark de Berg , Andrés López Martínez , Frits Spieksma

Connected clustering denotes a family of constrained clustering problems in which we are given a distance metric and an undirected connectivity graph $G$ that can be completely unrelated to the metric. The aim is to partition the $n$…

Data Structures and Algorithms · Computer Science 2025-11-25 Jan Eube , Heiko Röglin

Quantum annealing has the potential to find low energy solutions of NP-hard problems that can be expressed as quadratic unconstrained binary optimization problems. However, the hardware of the quantum annealer manufactured by D-Wave…

Quantum Physics · Physics 2024-01-22 Elijah Pelofske , Georg Hahn , Hristo N. Djidjev

We study finding and listing $k$-cliques in a graph, for constant $k\geq 3$, a fundamental problem of both theoretical and practical importance. Our main contribution is a new output-sensitive algorithm for listing $k$-cliques in graphs,…

Data Structures and Algorithms · Computer Science 2024-03-25 Mina Dalirrooyfard , Surya Mathialagan , Virginia Vassilevska Williams , Yinzhan Xu

We present a parallel k-clique listing algorithm with improved work bounds (for the same depth) in sparse graphs with low degeneracy or arboricity. We achieve this by introducing and analyzing a new pruning criterion for a backtracking…

Data Structures and Algorithms · Computer Science 2021-09-21 Lukas Gianinazzi , Maciej Besta , Yannick Schaffner , Torsten Hoefler

A hedge graph is a graph whose edge set has been partitioned into groups called hedges. Here we consider a generalization of the well-known \textsc{Cluster Deletion} problem, named \textsc{Hedge Cluster Deletion}. The task is to compute the…

Data Structures and Algorithms · Computer Science 2025-12-05 Athanasios L. Konstantinidis , Charis Papadopoulos , Georgios Velissaris

Motivated by hybrid graph representations, we introduce and study the following beyond-planarity problem, which we call $h$-Clique2Path Planarity: Given a graph $G$, whose vertices are partitioned into subsets of size at most $h$, each…

Data Structures and Algorithms · Computer Science 2018-08-29 Patrizio Angelini , Peter Eades , Seok-Hee Hong , Karsten Klein , Stephen Kobourov , Giuseppe Liotta , Alfredo Navarra , Alessandra Tappini

A $k$-defective clique is a relaxation of the traditional clique definition, allowing up to $k$ missing edges. This relaxation is crucial in various real-world applications such as link prediction, community detection, and social network…

Data Structures and Algorithms · Computer Science 2025-12-12 Jihoon Jang , Yehyun Nam , Kunsoo Park , Hyunjoon Kim

A k-clique covering of a simple graph G, is an edge covering of G by its cliques such that each vertex is contained in at most k cliques. The smallest k for which G admits a k-clique covering is called local clique cover number of G and is…

Combinatorics · Mathematics 2012-10-26 Ramin Javadi , Zeinab Maleki , Behnaz Omoomi

Clustering is a fundamental tool for analyzing large data sets. A rich body of work has been devoted to designing data-stream algorithms for the relevant optimization problems such as $k$-center, $k$-median, and $k$-means. Such algorithms…

Data Structures and Algorithms · Computer Science 2018-12-06 Kook Jin Ahn , Graham Cormode , Sudipto Guha , Andrew McGregor , Anthony Wirth

We study the fair k-set selection problem where we aim to select $k$ sets from a given set system such that the (weighted) occurrence times that each element appears in these $k$ selected sets are balanced, i.e., the maximum (weighted)…

Data Structures and Algorithms · Computer Science 2025-05-20 Shi Li , Chenyang Xu , Ruilong Zhang

In the EDGE CLIQUE COVER (ECC) problem, given a graph G and an integer k, we ask whether the edges of G can be covered with k complete subgraphs of G or, equivalently, whether G admits an intersection model on k-element universe. Gramm et…

Data Structures and Algorithms · Computer Science 2012-09-27 Marek Cygan , Marcin Pilipczuk , Michał Pilipczuk

We introduce a graph partitioning problem motivated by computational topology and propose two algorithms that produce approximate solutions. Specifically, given a weighted, undirected graph $G$ and a positive integer $k$, we desire to find…

Combinatorics · Mathematics 2019-07-04 Abdel-Rahman Madkour , Phillip Nadolny , Matthew Wright

Ashtiani et al. (NIPS 2016) introduced a semi-supervised framework for clustering (SSAC) where a learner is allowed to make same-cluster queries. More specifically, in their model, there is a query oracle that answers queries of the form…

Data Structures and Algorithms · Computer Science 2017-12-20 Nir Ailon , Anup Bhattacharya , Ragesh Jaiswal

The MaxClique problem, finding the largest complete subgraph in an Erd{\"o}s-R{\'e}nyi $G(N,p)$ random graph in the large $N$ limit, is a well-known example of a simple problem for which finding any approximate solution within a factor of…

Data Structures and Algorithms · Computer Science 2023-05-26 Raffaele Marino , Scott Kirkpatrick

In the $k$-Disjoint Shortest Paths ($k$-DSP) problem, we are given a weighted graph $G$ on $n$ nodes and $m$ edges with specified source vertices $s_1, \dots, s_k$, and target vertices $t_1, \dots, t_k$, and are tasked with determining if…

Data Structures and Algorithms · Computer Science 2024-05-13 Shyan Akmal , Virginia Vassilevska Williams , Nicole Wein

We study the problem of efficient exact partitioning of the hypergraphs generated by high-order planted models. A high-order planted model assumes some underlying cluster structures, and simulates high-order interactions by placing…

Machine Learning · Computer Science 2022-09-16 Chuyang Ke , Jean Honorio

In this paper, we study the Planted Clique problem in a semi-random model. Our model is inspired from the Feige-Kilian model [16] which has been studied in many other works [8,11,17,26,35,38] for a variety of graph problems. Our algorithm…

Data Structures and Algorithms · Computer Science 2025-12-09 Yash Khanna
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