76 citations · 387 across the 16 of their papers we have counts for
5 papers · 1 filter
RPT: Relational Pre-trained Transformer Is Almost All You Need towards Democratizing Data Preparation
Nan Tang, Ju Fan, Fangyi Li +5
Can AI help automate human-easy but computer-hard data preparation tasks that burden data scientists, practitioners, and crowd workers? We answer this question by presenting RPT, a…
Scalable Graph Neural Networks via Bidirectional Propagation
Ming Chen, Zhewei Wei, Bolin Ding +4
Graph Neural Networks (GNN) is an emerging field for learning on non-Euclidean data. Recently, there has been increased interest in designing GNN that scales to large graphs. Most…
TADOC: Text Analytics Directly on Compression
Feng Zhang, Jidong Zhai, Xipeng Shen +5
This article provides a comprehensive description of Text Analytics Directly on Compression (TADOC), which enables direct document analytics on compressed textual data. The article…
Relational Data Synthesis using Generative Adversarial Networks: A Design Space Exploration
Ju Fan, Tongyu Liu, Guoliang Li +3
The proliferation of big data has brought an urgent demand for privacy-preserving data publishing. Traditional solutions to this demand have limitations on effectively balancing th…
Exact Single-Source SimRank Computation on Large Graphs
Hanzhi Wang, Zhewei Wei, Ye Yuan +2
SimRank is a popular measurement for evaluating the node-to-node similarities based on the graph topology. In recent years, single-source and top- SimRank queries have received…