6 citations · 24 across the 13 of their papers we have counts for
5 papers · 1 filter
A Survey on Multi-Behavior Sequential Recommendation
Xiaoqing Chen, Zhitao Li, Weike Pan +1
Recommender systems is set up to address the issue of information overload in traditional information retrieval systems, which is focused on recommending information that is of mos…
GNN4FR: A Lossless GNN-based Federated Recommendation Framework
Guowei Wu, Weike Pan, Zhong Ming
Graph neural networks (GNNs) have gained wide popularity in recommender systems due to their capability to capture higher-order structure information among the nodes of users and i…
DPFormer: Learning Differentially Private Transformer on Long-Tailed Data
Youlong Ding, Xueyang Wu, Hao Wang +1
The Transformer has emerged as a versatile and effective architecture with broad applications. However, it still remains an open problem how to efficiently train a Transformer mode…
Bounding System-Induced Biases in Recommender Systems with A Randomized Dataset
Dugang Liu, Pengxiang Cheng, Zinan Lin +6
Debiased recommendation with a randomized dataset has shown very promising results in mitigating the system-induced biases. However, it still lacks more theoretical insights or an…
Self-Sampling Training and Evaluation for the Accuracy-Bias Tradeoff in Recommendation
Dugang Liu, Yang Qiao, Xing Tang +4
Research on debiased recommendation has shown promising results. However, some issues still need to be handled for its application in industrial recommendation. For example, most o…