83 citations · 203 across the 18 of their papers we have counts for
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cs.IR2022
On the Relationship Between Counterfactual Explainer and Recommender
Gang Liu, Zhihan Zhang, Zheng Ning +1
Recommender systems employ machine learning models to learn from historical data to predict the preferences of users. Deep neural network (DNN) models such as neural collaborative…
cs.LG2022★ 83 cited
Graph Rationalization with Environment-based Augmentations
Gang Liu, Tong Zhao, Jiaxin Xu +2
Rationale is defined as a subset of input features that best explains or supports the prediction by machine learning models. Rationale identification has improved the generalizabil…
cs.LG2022★ 42 cited
Graph Data Augmentation for Graph Machine Learning: A Survey
Tong Zhao, Wei Jin, Yozen Liu +5
Data augmentation has recently seen increased interest in graph machine learning given its demonstrated ability to improve model performance and generalization by added training da…