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Related papers: Weakly reflecting graph properties

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We prove the existence of a regular semigroup F(X) weakly generated by X such that all other regular semigroups weakly generated by X are homomorphic images of F(X). The semigroup F(X) is introduced by a presentation and the word problem…

Group Theory · Mathematics 2023-06-29 Luís Oliveira

The compactness phenomenon is one of the featured aspects of structuralism in mathematics. In simple and broad words, a compactness property holds in a structure if a related property is satisfied by sufficiently many substructures of that…

Logic · Mathematics 2024-08-29 Rahman Mohammadpour

In this paper, based on the contributions of Tucker (1983) and Seb{\H{o}} (1992), we generalize the concept of a sequential coloring of a graph to a framework in which the algorithm may use a coloring rule-base obtained from suitable…

Combinatorics · Mathematics 2008-12-31 Amir Daneshgar , Roozbeh Ebrahimi Soorchaei

A typical result in graph theory says that a graph $G$, satisfying certain conditions, has some property $\cal P$. Once such a theorem is established, it is natural to ask how strongly $G$ satisfies $\cal P$. Can one strengthen the result…

Combinatorics · Mathematics 2016-11-14 Benny Sudakov

The restricted hypercube-like graphs, variants of the hypercube, were proposed as desired interconnection networks of parallel systems. The matching preclusion number of a graph is the minimum number of edges whose deletion results in the…

Combinatorics · Mathematics 2020-01-23 Huazhong Lü , Tingzeng Wu

Graph-based methods have been demonstrated as one of the most effective approaches for semi-supervised learning, as they can exploit the connectivity patterns between labeled and unlabeled data samples to improve learning performance.…

Machine Learning · Computer Science 2019-07-01 Qimai Li , Xiao-Ming Wu , Han Liu , Xiaotong Zhang , Zhichao Guan

We investigate the representations and the structure of Hecke algebras associated to certain finite complex reflection groups. We first describe computational methods for the construction of irreducible representations of these algebras,…

Representation Theory · Mathematics 2019-02-20 Gunter Malle , Jean Michel

Graphs are naturally sparse objects that are used to study many problems involving networks, for example, distributed learning and graph signal processing. In some cases, the graph is not given, but must be learned from the problem and…

Machine Learning · Statistics 2017-08-31 Martin Sundin , Arun Venkitaraman , Magnus Jansson , Saikat Chatterjee

Existing weakly-supervised semantic segmentation methods using image-level annotations typically rely on initial responses to locate object regions. However, such response maps generated by the classification network usually focus on…

Computer Vision and Pattern Recognition · Computer Science 2020-08-05 Yu-Ting Chang , Qiaosong Wang , Wei-Chih Hung , Robinson Piramuthu , Yi-Hsuan Tsai , Ming-Hsuan Yang

In this thesis, the main objects of study are probability measures on the isomorphism classes of countable, connected rooted graphs. An important class of such measures is formed by unimodular measures, which satisfy a certain equation,…

Combinatorics · Mathematics 2014-01-29 Igor Artemenko

A large body of work has investigated the properties of graph neural networks and identified several limitations, particularly pertaining to their expressive power. Their inability to count certain patterns (e.g., cycles) in a graph lies at…

Machine Learning · Computer Science 2024-06-11 Emily Jin , Michael Bronstein , İsmail İlkan Ceylan , Matthias Lanzinger

Hypergraphs, increasingly utilised for modelling complex and diverse relationships in modern networks, gain much attention representing intricate higher-order interactions. Among various challenges, cohesive subgraph discovery is one of the…

Social and Information Networks · Computer Science 2025-12-30 Song Kim , Dahee Kim , Taejoon Han , Junghoon Kim , Hyun Ji Jeong , Jungeun Kim

In an era of unprecedented deluge of (mostly unstructured) data, graphs are proving more and more useful, across the sciences, as a flexible abstraction to capture complex relationships between complex objects. One of the main challenges…

Disordered Systems and Neural Networks · Physics 2016-10-17 Alaa Saade

Learning disentangled representations that correspond to factors of variation in real-world data is critical to interpretable and human-controllable machine learning. Recently, concerns about the viability of learning disentangled…

Machine Learning · Computer Science 2020-04-14 Rui Shu , Yining Chen , Abhishek Kumar , Stefano Ermon , Ben Poole

Verifying the veracity of claims requires reasoning over a large knowledge base, often in the form of corpora of trustworthy sources. A common approach consists in retrieving short portions of relevant text from the reference documents and…

Information Retrieval · Computer Science 2021-09-14 Misael Mongiovì , Aldo Gangemi

A graph theoretic perspective is taken for a range of phenomena in continuum physics in order to develop representations for analysis of large scale, high-fidelity solutions to these problems. Of interest are phenomena described by partial…

Computational Physics · Physics 2019-05-22 R. Banerjee , K. Sagiyama , G. H. Teichert , K. Garikipati

In this paper, we consider a question of sum-keeping about a multiplicative subsemigroup and its generator subsets in a semiring, and develop some elementary (collapse) process of the sum-keeping retraction through subsets until one minimal…

Number Theory · Mathematics 2025-04-04 Derong Qiu

In order to make argumentation-based inference contestable, it is crucial to explain what changes can achieve a desired (instead of the contested) inference result. To this end, we introduce strength change explanations for quantitative…

Multiagent Systems · Computer Science 2026-03-03 Timotheus Kampik , Xiang Yin , Nico Potyka , Francesca Toni

We consider the problem of offline, pool-based active semi-supervised learning on graphs. This problem is important when the labeled data is scarce and expensive whereas unlabeled data is easily available. The data points are represented by…

Machine Learning · Computer Science 2014-05-20 Akshay Gadde , Aamir Anis , Antonio Ortega

This paper proposes a blind detection problem for low pass graph signals. Without assuming knowledge of the exact graph topology, we aim to detect if a set of graph signal observations are generated from a low pass graph filter. Our problem…

Signal Processing · Electrical Eng. & Systems 2024-06-24 Chenyue Zhang , Yiran He , Hoi-To Wai