1 citations · 1 across the 7 of their papers we have counts for
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Relatron: Automating Relational Machine Learning over Relational Databases
Zhikai Chen, Han Xie, Jian Zhang +3
Predictive modeling over relational databases (RDBs) powers applications, yet remains challenging due to capturing both cross-table dependencies and complex feature interactions. R…
Empowering GNNs for Domain Adaptation via Denoising Target Graph
Haiyang Yu, Meng-Chieh Lee, Xiang song +2
We explore the node classification task in the context of graph domain adaptation, which uses both source and target graph structures along with source labels to enhance the genera…
AutoG: Towards automatic graph construction from tabular data
Zhikai Chen, Han Xie, Jian Zhang +4
Recent years have witnessed significant advancements in graph machine learning (GML), with its applications spanning numerous domains. However, the focus of GML has predominantly b…
GraphStorm: all-in-one graph machine learning framework for industry applications
Da Zheng, Xiang Song, Qi Zhu +13
Graph machine learning (GML) is effective in many business applications. However, making GML easy to use and applicable to industry applications with massive datasets remain challe…
NetInfoF Framework: Measuring and Exploiting Network Usable Information
Meng-Chieh Lee, Haiyang Yu, Jian Zhang +5
Given a node-attributed graph, and a graph task (link prediction or node classification), can we tell if a graph neural network (GNN) will perform well? More specifically, do the g…
ColdGuess: A General and Effective Relational Graph Convolutional Network to Tackle Cold Start Cases
Bo He, Xiang Song, Vincent Gao +1
Low-quality listings and bad actor behavior in online retail websites threatens e-commerce business as these result in sub-optimal buying experience and erode customer trust. When…