26 citations · 97 across the 13 of their papers we have counts for
5 papers · 1 filter
Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs
Chenxiao Yang, Qitian Wu, Jiahua Wang +1
Graph neural networks (GNNs), as the de-facto model class for representation learning on graphs, are built upon the multi-layer perceptrons (MLP) architecture with additional messa…
Geometric Knowledge Distillation: Topology Compression for Graph Neural Networks
Chenxiao Yang, Qitian Wu, Junchi Yan
We study a new paradigm of knowledge transfer that aims at encoding graph topological information into graph neural networks (GNNs) by distilling knowledge from a teacher GNN model…
Towards Out-of-Distribution Sequential Event Prediction: A Causal Treatment
Chenxiao Yang, Qitian Wu, Qingsong Wen +3
The goal of sequential event prediction is to estimate the next event based on a sequence of historical events, with applications to sequential recommendation, user behavior analys…
Trading Hard Negatives and True Negatives: A Debiased Contrastive Collaborative Filtering Approach
Chenxiao Yang, Qitian Wu, Jipeng Jin +3
Collaborative filtering (CF), as a standard method for recommendation with implicit feedback, tackles a semi-supervised learning problem where most interaction data are unobserved.…
Cross-Task Knowledge Distillation in Multi-Task Recommendation
Chenxiao Yang, Junwei Pan, Xiaofeng Gao +3
Multi-task learning (MTL) has been widely used in recommender systems, wherein predicting each type of user feedback on items (e.g, click, purchase) are treated as individual tasks…