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Mixed-Curvature Manifolds Interaction Learning for Knowledge Graph-aware Recommendation

Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023
As auxiliary collaborative signals, the entity connectivity and relation semanticity beneath knowledge graph (KG) triples can alleviate the data sparsity and cold-start issues of recommendation tasks.
Jihu Wang   +5 more
semanticscholar   +1 more source

Mixed graph colorings

Mathematical Methods of Operations Research, 1997
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Hansen, Pierre   +2 more
openaire   +1 more source

FreeScene: Mixed Graph Diffusion for 3D Scene Synthesis from Free Prompts

Computer Vision and Pattern Recognition
Controllability plays a crucial role in the practical applications of 3D indoor scene synthesis. Existing works either allow rough language-based control, that is convenient but lacks fine-grained scene customization, or employ graph-based control, which
Tongyuan Bai   +5 more
semanticscholar   +1 more source

Social Force Embedded Mixed Graph Convolutional Network for Multi-Class Trajectory Prediction

IEEE Transactions on Intelligent Vehicles
Accurate prediction of agent motion trajectories is crucial for ensuring the safety and reliability of autonomous driving systems. Current research predominantly focuses on traditional deep learning methods, including convolutional neural networks (CNNs)
Quancheng Du   +4 more
semanticscholar   +1 more source

Mixed hourglass graph

AIP Conference Proceedings, 2019
This article discusses a mixed graph called mixed hourglass graph. The adjacency of a mixed hourglass graph is coined from an hourglass matrix in which the matrix is obtained from quadratic interlocking factorization. Mixed hourglass graph is a weighted graph with loops, but replacing the weights of the graph with 1’s produce an unweighted mixed ...
Olayiwola Babarinsa   +1 more
openaire   +1 more source

Bounds on the nullity, the H-rank and the Hermitian energy of a mixed graph

Linear and multilinear algebra, 2019
Given an n-vertex graph G with maximum degree Δ, the mixed graph is constructed from G by orienting some of its edges, where G is called the underlying graph of . Let be the H-rank of and let be the independence number of G.
Wei Wei, Shuchao Li, Hongping Ma
semanticscholar   +1 more source

Mixed Loss Graph Attention Network for Few-Shot SAR Target Classification

IEEE Transactions on Geoscience and Remote Sensing, 2022
Restricted by the observation condition, synthetic aperture radar (SAR) automatic target classification based on deep learning usually suffers from insufficient training samples.
Minjia Yang   +3 more
semanticscholar   +1 more source

Mixed-Curvature Multi-Relational Graph Neural Network for Knowledge Graph Completion

The Web Conference, 2021
Knowledge graphs (KGs) have gradually become valuable assets for many AI applications. In a KG, a node denotes an entity, and an edge (or link) denotes a relationship between the entities represented by the nodes.
Shen Wang   +8 more
semanticscholar   +1 more source

The relation between the H-rank of a mixed graph and the independence number of its underlying graph

Linear and multilinear algebra, 2018
Let be a simple graph with vertex set and edge set . By orienting a subset of , we get a mixed graph . Let be the Hermitian-adjacency matrix of , the rank of , written as , is called the H-rank of . Denote by the dimension of cycle spaces of G, that is ,
Shuchao Li, Siqing Zhang, Baogen Xu
semanticscholar   +1 more source

Optimal Mixed Graph Augmentation

SIAM Journal on Computing, 1987
We consider an augmentation problem on mixed graphs that generalizes and unifies two augmentation problems considered by \textit{K. P. Eswaran} and \textit{R. E. Tarjan} [ibid. 5, 653-665 (1976; Zbl 0346.05112)]. The mixed augmentation problem has applications in the design of communication networks, and forms of mixed augmentation problem are central ...
openaire   +1 more source

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