Jiaoyan Chen

Knowledge-based Transfer Learning Explanation

2018 · arXiv (Cornell University)

Machine learning explanation can significantly boost machine learning's application in decision making, but the usability of current methods is limited in human-centric explanation, especially for transfer learning, an important machine learning branch that aims at …

Iteratively Learning Embeddings and Rules for Knowledge Graph Reasoning

2019 · Zurich Open Repository and Archive (University of Zurich)

Reasoning is essential for the development of large knowledge graphs, especially for completion, which aims to infer new triples based on existing ones. Both rules and embeddings can be used for knowledge graph reasoning and …

Ontology-guided Semantic Composition for Zero-Shot Learning

2020 · arXiv (Cornell University)

Zero-shot learning (ZSL) is a popular research problem that aims at predicting for those classes that have never appeared in the training stage by utilizing the inter-class relationship with some side information. In this study, …

Dual Box Embeddings for the Description Logic EL ⁺⁺

2024

OWL ontologies, whose formal semantics are rooted in Description Logic (DL), have been widely used for knowledge representation. Similar to Knowledge Graphs (KGs), ontologies are often incomplete, and maintaining and constructing them has proved challenging. …