Results 31 to 40 of about 287,840 (285)

Uniform graph embedding into metric spaces [PDF]

open access: yesКомпьютерные исследования и моделирование, 2012
The task of embedding an infinity countable graph into continuous metric space is considered. The concept of uniform embedding having no accumulation point in a set of vertex images and having all graph edge images of a limited length is introduced ...
A. V. Koganov
doaj   +1 more source

Embedding into Bipartite Graphs [PDF]

open access: yesSIAM Journal on Discrete Mathematics, 2010
16 pages, 2 ...
Böttcher, Julia   +2 more
openaire   +2 more sources

Exploring the Semantic Content of Unsupervised Graph Embeddings: An Empirical Study

open access: yesData Science and Engineering, 2019
Graph embeddings have become a key and widely used technique within the field of graph mining, proving to be successful across a broad range of domains including social, citation, transportation and biological. Unsupervised graph embedding techniques aim
Stephen Bonner   +5 more
doaj   +1 more source

Enriching Translation-Based Knowledge Graph Embeddings Through Continual Learning

open access: yesIEEE Access, 2018
This paper addresses an enrichment of translation-based knowledge graph embeddings. When new knowledge triples become available after a knowledge graph is embedded onto a vector space, the embedding should be enriched with the new triples, but without ...
Hyun-Je Song, Seong-Bae Park
doaj   +1 more source

Minor-Embedding in Adiabatic Quantum Computation: I. The Parameter Setting Problem [PDF]

open access: yes, 2008
We show that the NP-hard quadratic unconstrained binary optimization (QUBO) problem on a graph $G$ can be solved using an adiabatic quantum computer that implements an Ising spin-1/2 Hamiltonian, by reduction through minor-embedding of $G$ in the quantum
Choi, Vicky
core   +2 more sources

Attention-Aware Heterogeneous Graph Neural Network

open access: yesBig Data Mining and Analytics, 2021
As a powerful tool for elucidating the embedding representation of graph-structured data, Graph Neural Networks (GNNs), which are a series of powerful tools built on homogeneous networks, have been widely used in various data mining tasks.
Jintao Zhang, Quan Xu
doaj   +1 more source

Isometric embeddings of graphs [PDF]

open access: yesProceedings of the National Academy of Sciences, 1984
We prove that any finite undirected graph can be canonically embedded isometrically into a maximum cartesian product of irreducible factors.
Graham, R. L., Winkler, P. M.
openaire   +3 more sources

Learning Graph Embedding with Adversarial Training Methods

open access: yes, 2019
Graph embedding aims to transfer a graph into vectors to facilitate subsequent graph analytics tasks like link prediction and graph clustering. Most approaches on graph embedding focus on preserving the graph structure or minimizing the reconstruction ...
Fung, Sai-fu   +5 more
core   +1 more source

Minor-embedding in adiabatic quantum computation: II. Minor-universal graph design

open access: yes, 2010
In [Choi08], we introduced the notion of minor-embedding in adiabatic quantum optimization. A minor-embedding of a graph G in a quantum hardware graph U is a subgraph of U such that G can be obtained from it by contracting edges.
Choi, Vicky
core   +1 more source

Spectral embedding of graphs [PDF]

open access: yesPattern Recognition, 2003
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Luo, Bin   +2 more
openaire   +1 more source

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