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We study problems connected to first-order logic in graphs of bounded twin-width. Inspired by the approach of Bonnet et al. [FOCS 2020], we introduce a robust methodology of local types and describe their behavior in contraction sequences…

Logic in Computer Science · Computer Science 2022-06-17 Jakub Gajarský , Michał Pilipczuk , Wojciech Przybyszewski , Szymon Toruńczyk

In the recent research of data mining, frequent structures in a sequence of graphs have been studied intensively, and one of the main concern is changing structures along a sequence of graphs that can capture dynamic properties of data. On…

Data Structures and Algorithms · Computer Science 2012-06-28 Takeaki Uno , Yushi Uno

Exchangeable random graphs, which include some of the most widely studied network models, have emerged as the mainstay of statistical network analysis in recent years. Graphons, which are the central objects in graph limit theory, provide a…

Statistics Theory · Mathematics 2024-09-17 Anirban Chatterjee , Soham Dan , Bhaswar B. Bhattacharya

For a given graph $H$, its subdivisions carry the same topological structure. The existence of $H$-subdivisions within a graph $G$ has deep connections with topological, structural and extremal properties of $G$. One prominent example of…

Combinatorics · Mathematics 2023-08-22 Seonghyuk Im , Jaehoon Kim , Younjin Kim , Hong Liu

We present an innovative framework for traffic dynamics analysis using High-Order Evolving Graphs, designed to improve spatio-temporal representations in autonomous driving contexts. Our approach constructs temporal bidirectional bipartite…

Computer Vision and Pattern Recognition · Computer Science 2024-09-19 Aditya Humnabadkar , Arindam Sikdar , Benjamin Cave , Huaizhong Zhang , Paul Bakaki , Ardhendu Behera

The "Subset Sum problem" is a very well-known NP-complete problem. In this work, a top-k variation of the "Subset Sum problem" is considered. This problem has wide application in recommendation systems, where instead of k best objects the k…

Data Structures and Algorithms · Computer Science 2021-08-27 Biswajit Sanyal , Subhashis Majumder , Priya Ranjan Sinha Mahapatra

The problem of Subgraph Isomorphism is defined as follows: Given a pattern H and a host graph G on n vertices, does G contain a subgraph that is isomorphic to H? Eppstein [SODA 95, J'GAA 99] gives the first linear time algorithm for…

Data Structures and Algorithms · Computer Science 2009-09-28 Frederic Dorn

Every binary De~Bruijn sequence of order n satisfies a recursion 0=x_n+x_0+g(x_{n-1}, ..., x_1). Given a function f on (n-1) bits, let N(f; r) be the number of functions generating a De Bruijn sequence of order n which are obtained by…

Combinatorics · Mathematics 2017-05-23 Don Coppersmith , Robert C. Rhoades , Jeffrey M. VanderKam

An exact-match overlap graph of $n$ given strings of length $\ell$ is an edge-weighted graph in which each vertex is associated with a string and there is an edge $(x,y)$ of weight $\omega = \ell - |ov_{max}(x,y)|$ if and only if $\omega…

Data Structures and Algorithms · Computer Science 2010-09-22 Hieu Dinh , Sanguthevar Rajasekaran

We present kleuren, a novel assembly-free method to reconstruct phylogenetic trees using the Colored de Bruijn Graph. kleuren works by constructing the Colored de Bruijn Graph and then traversing it, finding bubble structures in the graph…

Populations and Evolution · Quantitative Biology 2018-04-24 Cole A. Lyman , M. Stanley Fujimoto , Anton Suvorov , Paul M. Bodily , Quinn Snell , Keith A. Crandall , Seth M. Bybee , Mark J. Clement

6G wireless technology is projected to adopt higher and wider frequency bands, enabled by highly directional beamforming. However, the vast bandwidths available also make the impact of beam squint in massive multiple input and multiple…

Signal Processing · Electrical Eng. & Systems 2025-01-28 Beier Li , Mai Vu

Training Graph Neural Networks (GNNs) on large graphs presents unique challenges due to the large memory and computing requirements. Distributed GNN training, where the graph is partitioned across multiple machines, is a common approach to…

Machine Learning · Computer Science 2024-06-26 Juan Cervino , Md Asadullah Turja , Hesham Mostafa , Nageen Himayat , Alejandro Ribeiro

Time series forecasting remains a challenging task for foundation models due to temporal heterogeneity, high dimensionality, and the lack of inherent symbolic structure. In this work, we propose DRAGON (Discrete Representation and Augmented…

Machine Learning · Computer Science 2025-07-04 Mert Onur Cakiroglu , Idil Bilge Altun , Mehmet Dalkilic , Elham Buxton , Hasan Kurban

Recently, the paradigm of pre-training and fine-tuning graph neural networks has been intensively studied and applied in a wide range of graph mining tasks. Its success is generally attributed to the structural consistency between…

Machine Learning · Computer Science 2023-12-22 Yifei Sun , Qi Zhu , Yang Yang , Chunping Wang , Tianyu Fan , Jiajun Zhu , Lei Chen

The problem of subgraph counting asks for the number of occurrences of a pattern graph $H$ as a subgraph of a host graph $G$ and is known to be computationally challenging: it is $\#W[1]$-hard even when $H$ is restricted to simple…

Data Structures and Algorithms · Computer Science 2026-03-27 Christine Awofeso , Patrick Greaves , Oded Lachish , Felix Reidl

In order to support the real-time interaction with LLMs and the instant search or the instant recommendation on social media, it becomes an imminent problem to build a k-NN graph or an indexing graph for the massive number of vectorized…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-01-21 Cheng Zhang , Wan-Lei Zhao , Shihai Xiao , Jiajie Yao , Xuecang Zhang

A de Bruijn covering code is a q-ary string S so that every q-ary string is at most R symbol changes from some n-word appearing consecutively in S. We introduce these codes and prove that they can have length close to the smallest possible…

Combinatorics · Mathematics 2007-07-16 Fan Chung , Joshua N. Cooper

De Bruijn graphs are essential for sequencing data analysis and must be efficiently constructed and stored for large-scale population studies. They also need to be dynamic to allow updates such as adding or removing edges and nodes.…

Data Structures and Algorithms · Computer Science 2024-06-19 Riccardo Nigrelli

Graph neural networks (GNNs) have significantly improved the representation power for graph-structured data. Despite of the recent success of GNNs, the graph convolution in most GNNs have two limitations. Since the graph convolution is…

Machine Learning · Computer Science 2021-12-30 Jinyoung Park , Sungdong Yoo , Jihwan Park , Hyunwoo J. Kim

Bayesian optimization (BO) is a powerful framework for optimizing expensive black-box objectives, yet extending it to graph-structured domains remains challenging due to the discrete and combinatorial nature of graphs. Existing approaches…

Machine Learning · Computer Science 2025-11-12 Shu Hong , Yongsheng Mei , Mahdi Imani , Tian Lan
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