256 citations · 329 across the 8 of their papers we have counts for
8 papers
Knowledge Association with Hyperbolic Knowledge Graph Embeddings
Zequn Sun, Muhao Chen, Wei Hu +3
Capturing associations for knowledge graphs (KGs) through entity alignment, entity type inference and other related tasks benefits NLP applications with comprehensive knowledge rep…
Global-to-Local Neural Networks for Document-Level Relation Extraction
Difeng Wang, Wei Hu, Ermei Cao +1
Relation extraction (RE) aims to identify the semantic relations between named entities in text. Recent years have witnessed it raised to the document level, which requires complex…
Rule-Guided Graph Neural Networks for Recommender Systems
Xinze Lyu, Guangyao Li, Jiacheng Huang +1
To alleviate the cold start problem caused by collaborative filtering in recommender systems, knowledge graphs (KGs) are increasingly employed by many methods as auxiliary resource…
Crowdsourced Collective Entity Resolution with Relational Match Propagation
Jiacheng Huang, Wei Hu, Zhifeng Bao +1
Knowledge bases (KBs) store rich yet heterogeneous entities and facts. Entity resolution (ER) aims to identify entities in KBs which refer to the same real-world object. Recent stu…
Open Knowledge Enrichment for Long-tail Entities
Ermei Cao, Difeng Wang, Jiacheng Huang +1
Knowledge bases (KBs) have gradually become a valuable asset for many AI applications. While many current KBs are quite large, they are widely acknowledged as incomplete, especiall…
Provable Benefit of Orthogonal Initialization in Optimizing Deep Linear Networks
Wei Hu, Lechao Xiao, Jeffrey Pennington
The selection of initial parameter values for gradient-based optimization of deep neural networks is one of the most impactful hyperparameter choices in deep learning systems, affe…