Binxuan Huang

Inductive Graph Representation Learning with Recurrent Graph Neural Networks

2019 · arXiv (Cornell University)

In this paper, we study the problem of node representation learning with graph neural networks. We present a graph neural network class named recurrent graph neural network (RGNN), that address the shortcomings of prior methods. …

Label-Efficient Self-Training for Attribute Extraction from Semi-Structured Web Documents

2022 · arXiv (Cornell University)

Extracting structured information from HTML documents is a long-studied problem with a broad range of applications, including knowledge base construction, faceted search, and personalized recommendation. Prior works rely on a few human-labeled web pages from …