Almost t-complementary uniform hypergraphs
Sign Up to like & getrecommendations! Published in 2019 at "Aequationes mathematicae"
DOI: 10.1007/s00010-018-0631-y
Abstract: An almost t-complementary k-hypergraph is a k-uniform hypergraph with vertex set V and edge set E for which there exists a permutation $$\theta \in Sym(V)$$θ∈Sym(V) such that the sets $$E, E^\theta , E^{\theta ^2}, \ldots… read more here.
Keywords: uniform hypergraphs; almost complementary; permutation; complementary uniform ... See more keywords
Sparse hypergraphs with low independence number
Sign Up to like & getrecommendations! Published in 2017 at "Combinatorica"
DOI: 10.1007/s00493-014-3219-8
Abstract: AbstractLet K4(3) denote the complete 3-uniform hypergraph on 4 vertices. Ajtai, Erdős, Komlós, and Szemerédi (1981) asked if there is a function ω(d)→∞ such that every 3-uniform, K4(3)-free hypergraph H with N vertices and average… read more here.
Keywords: hypergraph; hypergraphs low; independence number; sparse hypergraphs ... See more keywords
Domain adaptation network based on hypergraph regularized denoising autoencoder
Sign Up to like & getrecommendations! Published in 2017 at "Artificial Intelligence Review"
DOI: 10.1007/s10462-017-9576-0
Abstract: Domain adaptation learning aims to solve the classification problems of unlabeled target domain by using rich labeled samples in source domain, but there are three main problems: negative transfer, under adaptation and under fitting. Aiming… read more here.
Keywords: denoising autoencoder; network; hypergraph; domain adaptation ... See more keywords
Association rules redundancy processing algorithm based on hypergraph in data mining
Sign Up to like & getrecommendations! Published in 2018 at "Cluster Computing"
DOI: 10.1007/s10586-017-1632-7
Abstract: In order to achieve the research from individual data to data system and from passive verification of data to active discovery, taking high dimensional data oriented data mining technology as the research object, an association… read more here.
Keywords: association rules; data mining; hypergraph; association ... See more keywords
In the shadows of a hypergraph: looking for associated primes of powers of square-free monomial ideals
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Algebraic Combinatorics"
DOI: 10.1007/s10801-019-00915-5
Abstract: The aim of this paper is to study the associated primes of powers of square-free monomial ideals. Each square-free monomial ideal corresponds uniquely to a finite simple hypergraph via the cover ideal construction, and vice… read more here.
Keywords: free monomial; hypergraph; associated primes; square free ... See more keywords
DMH-FSL: Dual-Modal Hypergraph for Few-Shot Learning
Sign Up to like & getrecommendations! Published in 2022 at "Neural Processing Letters"
DOI: 10.1007/s11063-021-10684-7
Abstract: Large scale labeled samples are expensive and difficult to obtain, hence few-shot learning (FSL), only needing a small number of labeled samples, is a dedicated technology. Recently, the graph-based FSL approaches have attracted lots of… read more here.
Keywords: modal hypergraph; hypergraph; dmh fsl; shot learning ... See more keywords
Simplifying the computation of the spectrum of the complete k-uniform hypergraph
Sign Up to like & getrecommendations! Published in 2020 at "Linear Algebra and its Applications"
DOI: 10.1016/j.laa.2020.03.003
Abstract: Abstract In this paper, we give a method to simplify the computation of the spectrum of the complete k-uniform hypergraph with n vertices, which gives a partial answer to a question posed by Cooper and… read more here.
Keywords: spectrum complete; computation spectrum; hypergraph; uniform hypergraph ... See more keywords
Hypergraph Learning with Hyperedge Gating and Multiscale Topology Feature Learning for Predicting Disease-Related circRNAs
Sign Up to like & getrecommendations! Published in 2025 at "ACS Omega"
DOI: 10.1021/acsomega.5c04984
Abstract: As circular RNAs (circRNAs) play a crucial role in the onset and progression of diseases, identification of disease-related circRNAs can provide deep insights into the pathogenesis of complex diseases. Constructing graph learning-based models is a… read more here.
Keywords: disease; hyperedge; circrna disease; hypergraph ... See more keywords
DGHSA: derivative graph-based hypergraph structure attack
Sign Up to like & getrecommendations! Published in 2024 at "Scientific Reports"
DOI: 10.1038/s41598-024-79824-y
Abstract: Hypergraph Neural Networks (HGNNs) have been significantly successful in higher-order tasks. However, recent study have shown that they are also vulnerable to adversarial attacks like Graph Neural Networks. Attackers fool HGNNs by modifying node links… read more here.
Keywords: attack; based hypergraph; derivative graph; hypergraph ... See more keywords
Dual chain dynamic hypergraph convolution network for 3D human pose estimation
Sign Up to like & getrecommendations! Published in 2025 at "Scientific Reports"
DOI: 10.1038/s41598-025-22261-2
Abstract: Recently, various Graph Convolution Networks (GCNs) have been developed to represent the human skeleton using dynamic graph structures, enhancing the flexibility of node feature aggregation. However, the optimal graph structure can vary significantly across different… read more here.
Keywords: convolution; hypergraph; dynamic hypergraph; dual chain ... See more keywords
Hypergraph-driven spatial multimodal fusion for precise domain delineation and tumor microenvironment decoding.
Sign Up to like & getrecommendations! Published in 2025 at "Communications biology"
DOI: 10.1038/s42003-025-09312-0
Abstract: Recent advancements in spatial transcriptomics have transformed tumor microenvironment research by providing insights into cellular interactions and spatial heterogeneity. A fundamental challenge is the precise delineation of spatial domains. However, existing methods remain limited in… read more here.
Keywords: tumor microenvironment; delineation; microenvironment; hypergraph ... See more keywords