research
∙
09/09/2023
RecAD: Towards A Unified Library for Recommender Attack and Defense
In recent years, recommender systems have become a ubiquitous part of ou...
share
research
∙
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...
research
∙
08/26/2022
Causal Inference in Recommender Systems: A Survey and Future Directions
Existing recommender systems extract the user preference based on learni...
research
∙
02/22/2022
KuaiRec: A Fully-observed Dataset for Recommender Systems
Recommender systems are usually developed and evaluated on the historica...
research
∙
01/07/2022
On the Effectiveness of Sampled Softmax Loss for Item Recommendation
Learning objectives of recommender models remain largely unexplored. Mos...
research
∙
04/27/2021
A Survey on Neural Recommendation: From Collaborative Filtering to Content and Context Enriched Recommendation
Influenced by the stunning success of deep learning in computer vision a...
research
∙
09/08/2020
Adversarial Attack on Large Scale Graph
Recent studies have shown that graph neural networks are vulnerable agai...
research
∙
08/10/2020
A Survey on Large-scale Machine Learning
Machine learning can provide deep insights into data, allowing machines ...
research
∙
08/15/2018
A Simple but Hard-to-Beat Baseline for Session-based Recommendations
Convolutional Neural Networks (CNNs) models have been recently introduce...
research
∙
08/16/2017
