600 citations · 1.7k across the 29 of their papers we have counts for
5 papers · 1 filter
Conditional Denoising Diffusion for Sequential Recommendation
Yu Wang, Zhiwei Liu, Liangwei Yang +1
Generative models have attracted significant interest due to their ability to handle uncertainty by learning the inherent data distributions. However, two prominent generative mode…
Improving Contrastive Learning with Model Augmentation
Zhiwei Liu, Yongjun Chen, Jia Li +3
The sequential recommendation aims at predicting the next items in user behaviors, which can be solved by characterizing item relationships in sequences. Due to the data sparsity a…
Deep Fraud Detection on Non-attributed Graph
Chen Wang, Yingtong Dou, Min Chen +3
Fraud detection problems are usually formulated as a machine learning problem on a graph. Recently, Graph Neural Networks (GNNs) have shown solid performance on fraud detection. Th…
DSKReG: Differentiable Sampling on Knowledge Graph for Recommendation with Relational GNN
Yu Wang, Zhiwei Liu, Ziwei Fan +2
In the information explosion era, recommender systems (RSs) are widely studied and applied to discover user-preferred information. A RS performs poorly when suffering from the cold…
JSCN: Joint Spectral Convolutional Network for Cross Domain Recommendation
Zhiwei Liu, Lei Zheng, Jiawei Zhang +2
Cross-domain recommendation can alleviate the data sparsity problem in recommender systems. To transfer the knowledge from one domain to another, one can either utilize the neighbo…