Papers by Yuichi Yoshida

1 papers
RelWalk - A Latent Variable Model Approach to Knowledge Graph Embedding (2021.eacl-main)

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Challenge: Existing methods for embedding entities and relations in knowledge graphs are heuristically motivated and theoretical understanding of such embeddables is underdeveloped.
Approach: They extend the random walk model of word embeddings to Knowledge Graph Embeddings (KGEs) they propose a learning objective motivated by the theoretical analysis to learn KGEs from a given knowledge graph.
Outcome: The proposed learning objective is motivated by the theoretical analysis to learn KGEs from a given knowledge graph.

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