136 citations · 538 across the 49 of their papers we have counts for
8 papers · 1 filter
Addressing the Extreme Cold-Start Problem in Group Recommendation
Guo linxin, Tao yinghui, Gao Min +3
The task of recommending items to a group of users, a.k.a. group recommendation, is receiving increasing attention. However, the cold-start problem inherent in recommender systems…
Efficient Bi-Level Optimization for Recommendation Denoising
Zongwei Wang, Min Gao, Wentao Li +3
The acquisition of explicit user feedback (e.g., ratings) in real-world recommender systems is often hindered by the need for active user involvement. To mitigate this issue, impli…
Efficient On-Device Session-Based Recommendation
Xin Xia, Junliang Yu, Qinyong Wang +3
On-device session-based recommendation systems have been achieving increasing attention on account of the low energy/resource consumption and privacy protection while providing pro…
XSimGCL: Towards Extremely Simple Graph Contrastive Learning for Recommendation
Junliang Yu, Xin Xia, Tong Chen +3
Contrastive learning (CL) has recently been demonstrated critical in improving recommendation performance. The underlying principle of CL-based recommendation models is to ensure t…
On-Device Next-Item Recommendation with Self-Supervised Knowledge Distillation
Xin Xia, Hongzhi Yin, Junliang Yu +3
Modern recommender systems operate in a fully server-based fashion. To cater to millions of users, the frequent model maintaining and the high-speed processing for concurrent user…
Self-Supervised Learning for Recommender Systems: A Survey
Junliang Yu, Hongzhi Yin, Xin Xia +3
In recent years, neural architecture-based recommender systems have achieved tremendous success, but they still fall short of expectation when dealing with highly sparse data. Self…
Predictive and Contrastive: Dual-Auxiliary Learning for Recommendation
Yinghui Tao, Min Gao, Junliang Yu +3
Self-supervised learning (SSL) recently has achieved outstanding success on recommendation. By setting up an auxiliary task (either predictive or contrastive), SSL can discover sup…
Who Are the Best Adopters? User Selection Model for Free Trial Item Promotion
Shiqi Wang, Chongming Gao, Min Gao +3
With the increasingly fierce market competition, offering a free trial has become a potent stimuli strategy to promote products and attract users. By providing users with opportuni…