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A graph $G$ is cordial if there exists a function $f$ from the vertices of $G$ to $\{0,1\}$ such that the number of vertices labelled $0$ and the number of vertices labelled $1$ differ by at most $1$, and if we assign to each edge $xy$ the…

Combinatorics · Mathematics 2025-03-04 Anand Brahmbhatt , Kartikeya Rai , Amitabha Tripathi

An important problem in multi-label classification is to capture label patterns or underlying structures that have an impact on such patterns. This paper addresses one such problem, namely how to exploit hierarchical structures over labels.…

Machine Learning · Computer Science 2015-04-17 Jinseok Nam , Johannes Fürnkranz

Given a graph $G$ with $n$ vertices and a bijective labeling of the vertices using the integers $1,2,\ldots, n$, we say $G$ has a peak at vertex $v$ if the degree of $v$ is greater than or equal to 2, and if the label on $v$ is larger than…

Given a set of nonempty subsets of some universal set, their intersection graph is defined as the graph with one vertex for each set and two vertices are adjacent precisely when their representing sets have non-empty intersection. Sometimes…

General Mathematics · Mathematics 2016-02-15 Mahipal Jadeja , Rahul Muthu , Sunitha V

In this paper we focus on the following constrained reachability problem over edge-labeled graphs like RDF -- "given source node x, destination node y, and a sequence of edge labels (a, b, c, d), is there a path between the two nodes such…

Databases · Computer Science 2012-03-14 Medha Atre , Vineet Chaoji , Mohammed J. Zaki

In this paper, we consider the problem of the recognition of various kinds of orderings produced by graph searches. To this aim, we introduce a new framework, the Tie-Breaking Label Search (TBLS), in order to handle a broad variety of…

Data Structures and Algorithms · Computer Science 2015-01-27 Derek G. Corneil , Jeremie Dusart , Michel Habib , Fabien de Montgolfier

Many real-world applications of image recognition require multi-label learning, whose goal is to find all labels in an image. Thus, robustness of such systems to adversarial image perturbations is extremely important. However, despite a…

Computer Vision and Pattern Recognition · Computer Science 2022-07-13 Hassan Mahmood , Ehsan Elhamifar

Binary classification problems can be naturally modeled as bipartite graphs, where we attempt to classify right nodes based on their left adjacencies. We consider the case of labeled bipartite graphs in which some labels and edges are not…

Combinatorics · Mathematics 2018-11-13 R. W. R. Darling , Mark L. Velednitsky

We show how to assign labels of size $\tilde O(1)$ to the vertices of a directed planar graph $G$, such that from the labels of any three vertices $s,t,f$ we can deduce in $\tilde O(1)$ time whether $t$ is reachable from $s$ in the graph…

Data Structures and Algorithms · Computer Science 2023-07-17 Shiri Chechik , Shay Mozes , Oren Weimann

A $(0,1)$-labeling of a set is said to be friendly if the number of elements of the set labeled 0 and the number labeled 1 differ by at most 1. Let $g$ be a labeling of the edge set of a graph that is induced by a labeling $f$ of the vertex…

Combinatorics · Mathematics 2022-12-13 LeRoy B. Beasley

Label distribution learning can characterize the polysemy of an instance through label distributions. However, some noise and uncertainty may be introduced into the label space when processing label distribution data due to artificial or…

Machine Learning · Computer Science 2022-10-18 Qimeng Guo , Zhuoran Zheng , Xiuyi Jia , Liancheng Xu

This paper considers the problem of efficiently answering reachability queries over views of provenance graphs, derived from executions of workflows that may include recursion. Such views include composite modules and model fine-grained…

Databases · Computer Science 2012-08-02 Zhuowei Bao , Susan B. Davidson , Tova Milo

Label propagation is a powerful and flexible semi-supervised learning technique on graphs. Neural networks, on the other hand, have proven track records in many supervised learning tasks. In this work, we propose a training framework with a…

Machine Learning · Computer Science 2017-03-16 Thang D. Bui , Sujith Ravi , Vivek Ramavajjala

The generalized list $T$-coloring is a common generalization of many graph coloring models, including classical coloring, $L(p,q)$-labeling, channel assignment and $T$-coloring. Every vertex from the input graph has a list of permitted…

Discrete Mathematics · Computer Science 2013-12-04 Konstanty Junosza-Szaniawski , Paweł Rzążewski

A total weighting of a graph $G$ is a mapping $f$ which assigns to each element $z \in V(G) \cup E(G)$ a real number $f(z)$ as its weight. The vertex sum of $v$ with respect to $f$ is $\phi_f(v)=\sum_{e \in E(v)}f(e)+f(v)$. A total…

Combinatorics · Mathematics 2015-10-06 Tsai-Lien Wong , Xuding Zhu

Property graphs can be used to represent heterogeneous networks with labeled (attributed) vertices and edges. Given a property graph, simulating another graph with same or greater size with the same statistical properties with respect to…

Social and Information Networks · Computer Science 2019-07-18 Arun V. Sathanur , Sutanay Choudhury , Cliff Joslyn , Sumit Purohit

This paper initializes the study of {\em range subgraph counting} and {\em range subgraph listing}, both of which are motivated by the significant demands in practice to perform graph analytics on subgraphs pertinent to only selected, as…

Data Structures and Algorithms · Computer Science 2023-01-10 Shiyuan Deng , Shangqi Lu , Yufei Tao

A vertex $v$ is called an AR-vertex, if $v$ has distinct edge weight sums for each distinct subset of edges incident on $v$. i.e., if $\{x_1,x_2,\dots,x_k\}$ are the edge labels of the edges incident on $v$, then the $2^k$ subset sums are…

Combinatorics · Mathematics 2025-02-18 Arun J Manattu , Aparna Lakshmanan S

In this paper we introduce a generalization of the well known concept of a graceful labeling. Given a graph G with e=dm edges, we call d-graceful labeling of G an injective function from V(G) to the set {0,1,2,..., d(m+1)-1} such that…

Combinatorics · Mathematics 2012-09-10 A. Pasotti

Graph Neural Networks (GNNs) have shown remarkable capabilities in learning from graph-structured data with various applications such as social analysis and bioinformatics. However, the presence of label noise in real scenarios poses a…

Machine Learning · Computer Science 2026-01-27 Wei Ju , Wei Zhang , Siyu Yi , Zhengyang Mao , Yifan Wang , Jingyang Yuan , Zhiping Xiao , Ziyue Qiao , Ming Zhang