Hai Zhu

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 …

COY ARJATE ADruSTED RESPONSE ADAPTIVE RANDOMIZATION DESIGNS WITH TARGETED LEARNING

2019 · Digital Commons-TMC (Texas Medical Center)

Since Food and Drug Administration (FDA) issued the very first draft guidance in 2010, adaptive designs have been considered to be one of the most promising approaches to make drug development more efficient and less …

Label-Free Distant Supervision for Relation Extraction via Knowledge Graph Embedding

2018

Distant supervision is an effective method to generate large scale labeled data for relation extraction, which assumes that if a pair of entities appears in some relation of a Knowledge Graph (KG), all sentences containing …