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Aug 16, 2023 · This paper proposes an inductive method, FastHGE to learn node representation more efficiently and generalize to new nodes more easily.
This paper proposes an inductive method, FastHGE to learn node representation more efficiently and generalize to new nodes more easily.
[PDF] A Subspace Constraint based Approach for Fast Hierarchical ...
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Dec 15, 2022 · This paper focuses on the hierarchy preserving graph embedding method for complicated networks with high efficiency. To preserve structural ...
Hierarchy preserving network embedding is a representation learning method that project nodes into feature space by preserving the hierarchy property of ...
An inductive method, FastHGE is proposed to learn node representation more efficiently and generalize to new nodes more easily, based on transductive ...
Jul 20, 2024 · Minghe Yu, Xu Chen, Xinhao Gu, Hengyu Liu, Lun Du: A subspace constraint based approach for fast hierarchical graph embedding.
In this paper, we propose an inductive method, FastHGE, to learn node representations more efficiently and generalize to new nodes more easily.
Missing: approach | Show results with:approach
A subspace constraint based approach for fast hierarchical graph embedding. Minghe Yu; Xu Chen; Lun Du. OriginalPaper 16 August 2023 Pages: 3691 - 3705 ...
2023. A subspace constraint based approach for fast hierarchical graph embedding. M Yu, X Chen, X Gu, H Liu, L Du. World Wide Web 26 (5), 3691-3705, 2023. 1 ...
In this paper, we propose an inductive learning method. FastHGE to learn node representations much more effi- ciently while preserving the subspace constraints ...
Missing: approach | Show results with:approach