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05/24/2023
How Graph Convolutions Amplify Popularity Bias for Recommendation?
Graph convolutional networks (GCNs) have become prevalent in recommender...
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04/06/2023
GIF: A General Graph Unlearning Strategy via Influence Function
With the greater emphasis on privacy and security in our society, the pr...
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02/09/2023
Adap-Ï„: Adaptively Modulating Embedding Magnitude for Recommendation
Recent years have witnessed the great successes of embedding-based metho...
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11/05/2022
Adversarial Causal Augmentation for Graph Covariate Shift
Out-of-distribution (OOD) generalization on graphs is drawing widespread...
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04/26/2022
Cross Pairwise Ranking for Unbiased Item Recommendation
Most recommender systems optimize the model on observed interaction data...
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01/07/2022
On the Effectiveness of Sampled Softmax Loss for Item Recommendation
Learning objectives of recommender models remain largely unexplored. Mos...
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12/30/2021
Deconfounded Training for Graph Neural Networks
Learning powerful representations is one central theme of graph neural n...
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10/21/2020
Self-supervised Graph Learning for Recommendation
Representation learning on user-item graph for recommendation has evolve...
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01/30/2020
