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Here we study the problem of learning labels for large text corpora where each text can be assigned a variable number of labels. The problem might seem trivial when the label dimensionality is small and can be easily solved using a series…

Machine Learning · Computer Science 2016-11-02 Sayantan Dasgupta

A numbering $f$ of a graph $G$ of order $n$ is a labeling that assigns distinct elements of the set $\left\{ 1,2,\ldots ,n\right\} $ to the vertices of $G$. The strength $\textrm{str}_{f}\left( G\right)$ of a numbering $f:V\left( G\right)…

Combinatorics · Mathematics 2023-04-04 Yukio Takahashi , Rikio Ichishima , Francesc A. Muntaner-Batle

Recent works have shown that exploiting unlabeled data through label propagation can substantially reduce the labeling cost, which has been a critical issue in developing visual recognition models. Yet, how to propagate labels reliably,…

Computer Vision and Pattern Recognition · Computer Science 2020-07-20 Lei Yang , Qingqiu Huang , Huaiyi Huang , Linning Xu , Dahua Lin

A coprime labeling of a graph of order $n$ is an assignment of distinct positive integer labels in which adjacent vertices have relatively prime labels. Restricting labels to only the set $1$ to $n$ results in a prime labeling. In this…

Combinatorics · Mathematics 2019-08-19 John Asplund , N. Bradley Fox

Graph labeling is a technique that assigns unique labels or weights to the vertices or edges of a graph, often used to analyze and solve various graph-related problems. There are few methods with certain limitations conducted by researchers…

Discrete Mathematics · Computer Science 2024-03-28 Arafat Islam , Md. Imtiaz Habib

We consider a family of problems that are concerned about making predictions for the majority of unlabeled, graph-structured data samples based on a small proportion of labeled samples. Relational information among the data samples, often…

Machine Learning · Computer Science 2019-11-05 Jiaqi Ma , Weijing Tang , Ji Zhu , Qiaozhu Mei

For an arbitrary finite family of graphs, the distance labeling problem asks to assign labels to all nodes of every graph in the family in a way that allows one to recover the distance between any two nodes of any graph from their labels.…

Combinatorics · Mathematics 2023-08-30 Arseny M. Shur , Mikhail Rubinchik

An edge labeling of a graph distinguishes neighbors by sets (multisets, resp.), if for any two adjacent vertices $u$ and $v$ the sets (multisets, resp.) of labels appearing on edges incident to $u$ and $v$ are different. In an analogous way…

Discrete Mathematics · Computer Science 2018-04-30 Karolina Okrasa , Paweł Rzążewski

Approximate proof labeling schemes were introduced by \\Censor-Hillel, Paz and Perry \cite{CPP}. Roughly speaking, a graph property~$\cP$ can be verified by an approximate proof labeling scheme in constant-time if the vertices of a graph…

Combinatorics · Mathematics 2022-05-25 Gábor Elek

Node classification on graphs is a significant task with a wide range of applications, including social analysis and anomaly detection. Even though graph neural networks (GNNs) have produced promising results on this task, current…

Machine Learning · Computer Science 2023-06-16 Jingyang Yuan , Xiao Luo , Yifang Qin , Yusheng Zhao , Wei Ju , Ming Zhang

A distance labeling scheme is an assignment of bit-labels to the vertices of an undirected, unweighted graph such that the distance between any pair of vertices can be decoded solely from their labels. We propose a series of new labeling…

Data Structures and Algorithms · Computer Science 2016-07-21 Paweł Gawrychowski , Adrian Kosowski , Przemysław Uznański

The implicit graph conjecture states that every sufficiently small, hereditary graph class has a labeling scheme with a polynomial-time computable label decoder. We approach this conjecture by investigating classes of label decoders defined…

Computational Complexity · Computer Science 2018-02-02 Maurice Chandoo

Finding densely connected groups of nodes in networks is a widely used tool for analysis in graph mining. A popular choice for finding such groups is to find subgraphs with a high average degree. While useful, interpreting such subgraphs…

Social and Information Networks · Computer Science 2023-09-08 Iiro Kumpulainen , Nikolaj Tatti

For a flexible labeling of a graph, it is possible to construct infinitely many non-equivalent realizations keeping the distances of connected points constant. We give a combinatorial characterization of graphs that have flexible labelings.…

Combinatorics · Mathematics 2019-09-17 Georg Grasegger , Jan Legerský , Josef Schicho

This paper deals with the $\lambda$-labeling and $L(2,1)$-coloring of simple graphs. A $\lambda$-labeling of a graph $G$ is any labeling of the vertices of $G$ with different labels such that any two adjacent vertices receive labels which…

Combinatorics · Mathematics 2024-03-05 Manouchehr Zaker

A class of graphs admits an adjacency labeling scheme of size $b(n)$, if the vertices in each of its $n$-vertex graphs can be assigned binary strings (called labels) of length $b(n)$ so that the adjacency of two vertices can be determined…

Combinatorics · Mathematics 2024-02-21 Édouard Bonnet , Julien Duron , John Sylvester , Viktor Zamaraev , Maksim Zhukovskii

The graph exploration problem is to visit all the nodes of a connected graph by a mobile entity, e.g., a robot. The robot has no a priori knowledge of the topology of the graph or of its size. Cohen et al. \cite{Ilcinkas08} introduced label…

Data Structures and Algorithms · Computer Science 2012-05-01 Meng Zhang , Yi Zhang , Jijun Tang

For $k\in\mathbb{Z}^+$ and $G$ a simple connected graph, a $k$-radio labeling $f:V_G\to\Z^+$ of $G$ requires all pairs of distinct vertices $u$ and $v$ to satisfy $|f(u)-f(v)|\geq k+1-d(u,v)$. When $k=1$, this requirement gives rise to the…

Combinatorics · Mathematics 2012-12-11 Amanda Niedzialomski

Graph labellings have been a very fruitful area of research in the last four decades. However, despite the staggering number of papers published in the field (over 1000), few general results are available, and most papers deal with…

Prior knowledge and symbolic rules in machine learning are often expressed in the form of label constraints, especially in structured prediction problems. In this work, we compare two common strategies for encoding label constraints in a…

Machine Learning · Computer Science 2023-07-11 Kaifu Wang , Hangfeng He , Tin D. Nguyen , Piyush Kumar , Dan Roth