Results 121 to 130 of about 56,162 (272)

Hall's marriage theorem

open access: yesJournal of the London Mathematical Society, Volume 113, Issue 1, January 2026.
Abstract In 1935, Philip Hall published what is often referred to as ‘Hall's marriage theorem’ in a short paper (P. Hall, J. Lond. Math. Soc. (1) 10 (1935), no. 1, 26–30.) This paper has been very influential. I state the theorem and outline Hall's proof, together with some equivalent (or stronger) earlier results, and proceed to discuss some the many ...
Peter J. Cameron
wiley   +1 more source

q-Rung Orthopair Fuzzy Hypergraphs with Applications

open access: yesMathematics, 2019
The concept of q-rung orthopair fuzzy sets generalizes the notions of intuitionistic fuzzy sets and Pythagorean fuzzy sets to describe complicated uncertain information more effectively.
Anam Luqman   +2 more
doaj   +1 more source

Eigenvalues of Non-Regular Linear-Quasirandom Hypergraphs [PDF]

open access: yes, 2014
Chung, Graham, and Wilson proved that a graph is quasirandom if and only if there is a large gap between its first and second largest eigenvalue. Recently, the authors extended this characterization to k-uniform hypergraphs, but only for the so-called ...
Lenz, John, Mubayi, Dhruv
core  

Colorful Subhypergraphs in Kneser Hypergraphs [PDF]

open access: yesThe Electronic Journal of Combinatorics, 2014
Using a $\mathbb{Z}_q$-generalization of a theorem of Ky Fan, we extend to Kneser hypergraphs a theorem of Simonyi and Tardos that ensures the existence of multicolored complete bipartite graphs in any proper coloring of a Kneser graph. It allows to derive a lower bound for the local chromatic number of Kneser hypergraphs (using a natural definition of
openaire   +3 more sources

CoRoFR: Community Detection of Feature Graph Improves Feature Selection Using Robust Fuzzy Rough Set

open access: yesAdvanced Intelligent Systems, Volume 7, Issue 12, December 2025.
In machine learning, features often function as communities in many tasks, especially in medicine. However, existing feature selection methods struggle to mine feature collaborations, which can boost predictive performance. Moreover, they are noise‐sensitive, leading to suboptimal feature selection and accuracy degradation.
Duanyang Feng   +4 more
wiley   +1 more source

Maximum Shattering

open access: yesJournal of Combinatorial Designs, Volume 33, Issue 12, Page 456-470, December 2025.
ABSTRACT A family ℱ of subsets of [ n ] = { 1 , 2 , … , n } shatters a set A ⊆ [ n ] if for every A ′ ⊆ A, there is an F ∈ ℱ such that F ∩ A = A '. We develop a framework to analyze f ( n , k , d ), the maximum possible number of subsets of [ n ] of size d that can be shattered by a family of size k.
Noga Alon   +2 more
wiley   +1 more source

PLNet: Persistent Laplacian neural network for protein–protein binding free energy prediction

open access: yesProtein Science, Volume 34, Issue 12, December 2025.
Abstract Recent advances in topology‐based modeling have greatly improved molecular prediction tasks, particularly in protein–ligand binding affinity. However, when the focus shifts to predicting protein–protein interactions (PPIs) binding free energy, the question becomes significantly more challenging due to the ineffective use of topological ...
Xingjian Xu   +3 more
wiley   +1 more source

Modularity Definition and Optimization Algorithm for Community Detection in Signed Hypergraphs

open access: yesComplexity
The analysis of super-dyadic relations through hypergraphs is gradually gaining attention, with its community structure analysis playing a crucial role in computational social science.
Wei Du, Guangyu Li
doaj   +1 more source

Analysis of hub parameters in fuzzy hypergraphs extending to intuitionistic fuzzy threshold hypergraphs: Applications in designing transport networks in amusement parks using hub hyperpaths [PDF]

open access: yesNotes on IFS
A hypergraph is a generalization of a graph where an edge can connect any number of vertices. In this paper, many different aspects of fuzzy hypergraphs and their applications are examined.
K. K. Myithili, C. Nandhini
doaj   +1 more source

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