67 citations · 109 across the 14 of their papers we have counts for
4 papers · 1 filter
Accelerating the Surrogate Retraining for Poisoning Attacks against Recommender Systems
Yunfan Wu, Qi Cao, Shuchang Tao +3
Recent studies have demonstrated the vulnerability of recommender systems to data poisoning attacks, where adversaries inject carefully crafted fake user interactions into the trai…
Robust Recommender System: A Survey and Future Directions
Kaike Zhang, Qi Cao, Fei Sun +4
With the rapid growth of information, recommender systems have become integral for providing personalized suggestions and overcoming information overload. However, their practical…
Popularity Debiasing from Exposure to Interaction in Collaborative Filtering
Yuanhao Liu, Qi Cao, Huawei Shen +3
Recommender systems often suffer from popularity bias, where popular items are overly recommended while sacrificing unpopular items. Existing researches generally focus on ensuring…
INMO: A Model-Agnostic and Scalable Module for Inductive Collaborative Filtering
Yunfan Wu, Qi Cao, Huawei Shen +2
Collaborative filtering is one of the most common scenarios and popular research topics in recommender systems. Among existing methods, latent factor models, i.e., learning a speci…