Results 71 to 80 of about 653 (189)

CF‐SBERTHet: Collaborative and Textual Knowledge Enhanced Semantic Graphs for Sparse Recommendations

open access: yesExpert Systems, Volume 43, Issue 7, July 2026.
ABSTRACT Modern e‐commerce platforms face a critical challenge: delivering accurate recommendations under extreme user–item interaction sparsity, where textual context remains systematically underutilised. Existing collaborative filtering methods degrade sharply in sparse settings, while semantic approaches fail to capture collaborative patterns ...
He Ma   +7 more
wiley   +1 more source

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

open access: yesAdvanced Science, Volume 13, Issue 35, 24 June 2026.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu   +4 more
wiley   +1 more source

A Tight Bound for Hyperaph Regularity

open access: yesGeometric and Functional Analysis, 2019
This manuscript contains the proof of the main result of arXiv:1907.07639 when specialized to 3-uniform ...
Moshkovitz, Guy, Shapira, Asaf
openaire   +5 more sources

New strong colouring of hypergraphs

open access: yesLe Matematiche, 2011
We define a new colouring for a hypergraph, in particular for a graph. Such a method is a partition of the vertex-set of a hypergraph, in particular of a graph.
Sandro Rajola, Maria Scafati Tallini
doaj  

Improved Multiscale Structural Mapping with Supervertex Vision Transformer for the Detection of Alzheimer's Disease Neurodegeneration

open access: yesHuman Brain Mapping, Volume 47, Issue 8, June 1, 2026.
We propose MSSM+, an extension of multiscale structural mapping (MSSM), together with surface supervertex mapping (SSVM) and a Supervertex Vision Transformer (SV‐ViT). Together, these methods exhibited better performance in detecting Alzheimer's disease and less variability across MR vendors than MSSM.
Geonwoo Baek   +3 more
wiley   +1 more source

An Algorithmic Version of the Hypergraph Regularity Method [PDF]

open access: yesSIAM Journal on Computing, 2005
Extending the Szemeredi regularity lemma for graphs, P. Frankl and V. Rodl [Random Structures Algorithms, 20 (2002), pp. 131-164] established a 3-graph regularity lemma triple systems ${\cal G}_n$ admit bounded partitions of their edge sets, most classes of which consist of regularly distributed triples.
Penny E. Haxell   +2 more
openaire   +1 more source

Two‐Round Ramsey Games on Random Graphs

open access: yesRandom Structures &Algorithms, Volume 68, Issue 3, May 2026.
ABSTRACT Motivated by the investigation of sharpness of thresholds for Ramsey properties in random graphs, Friedgut, Kohayakawa, Rödl, Ruciński and Tetali introduced two variants of a single‐player game whose goal is to colour the edges of a random graph, in an online fashion, so as not to create a monochromatic triangle.
Yahav Alon   +2 more
wiley   +1 more source

Regular Subgraphs of Linear Hypergraphs

open access: yesInternational Mathematics Research Notices
Abstract We prove that the maximum number of edges in a 3-uniform linear hypergraph on $n$ vertices containing no 2-regular subhypergraph is $n^{1+o(1)}$. This resolves a conjecture of Dellamonica, Haxell, Łuczak, Mubayi, Nagle, Person, Rödl, Schacht, and Verstraëte.
Janzer, Oliver   +2 more
openaire   +5 more sources

Hypergraph models of metabolism

open access: yes, 2014
In this paper, we employ a directed hypergraph model to investigate the extent to which environmental variability influences the set of available biochemical reactions within a living cell.
Crofts, JJ, Chuzhanova, N, Pearcy, N
core  

Erdős‐Rogers Functions for Arbitrary Pairs of Graphs

open access: yesRandom Structures &Algorithms, Volume 68, Issue 3, May 2026.
ABSTRACT Let fF,G(n)$$ {f}_{F,G}(n) $$ be the largest size of an induced F$$ F $$‐free subgraph that every n$$ n $$‐vertex G$$ G $$‐free graph is guaranteed to contain. We prove that for any triangle‐free graph F$$ F $$, fF,K3(n)=fK2,K3(n)1+o(1)=n12+o(1).$$ {f}_{F,{K}_3}(n)={f}_{K_2,{K}_3}{(n)}^{1+o(1)}={n}^{\frac{1}{2}+o(1)}. $$Along the way we give a
Dhruv Mubayi, Jacques Verstraëte
wiley   +1 more source

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