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20182023
most citedTabGNN: Multiplex Graph Neural Network for Tabular Data Prediction

16 citations · 27 across the 4 of their papers we have counts for

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5 papers · 1 filter

cs.LG20233 cited

Combating Bilateral Edge Noise for Robust Link Prediction

Zhanke Zhou, Jiangchao Yao, Jiaxu Liu +6

Although link prediction on graphs has achieved great success with the development of graph neural networks (GNNs), the potential robustness under the edge noise is still less inve…

cs.LG2023

Exploring Model Dynamics for Accumulative Poisoning Discovery

Jianing Zhu, Xiawei Guo, Jiangchao Yao +6

Adversarial poisoning attacks pose huge threats to various machine learning applications. Especially, the recent accumulative poisoning attacks show that it is possible to achieve…

cs.LG202116 cited

TabGNN: Multiplex Graph Neural Network for Tabular Data Prediction

Xiawei Guo, Yuhan Quan, Huan Zhao +3

Tabular data prediction (TDP) is one of the most popular industrial applications, and various methods have been designed to improve the prediction performance. However, existing wo…

cs.LG20218 cited

Task-wise Split Gradient Boosting Trees for Multi-center Diabetes Prediction

Mingcheng Chen, Zhenghui Wang, Zhiyun Zhao +14

Diabetes prediction is an important data science application in the social healthcare domain. There exist two main challenges in the diabetes prediction task: data heterogeneity si…

cs.LG2018

Differential Private Stack Generalization with an Application to Diabetes Prediction

Quanming Yao, Xiawei Guo, James T. Kwok +4

To meet the standard of differential privacy, noise is usually added into the original data, which inevitably deteriorates the predicting performance of subsequent learning algorit…