6 citations · 8 across the 5 of their papers we have counts for
5 papers
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…
Path-Based Reasoning over Heterogeneous Networks for Recommendation via Bidirectional Modeling
Junwei Zhang, Min Gao, Junliang Yu +3
Heterogeneous Information Network (HIN) is a natural and general representation of data in recommender systems. Combining HIN and recommender systems can not only help model user b…
Recommender Systems Based on Generative Adversarial Networks: A Problem-Driven Perspective
Min Gao, Junwei Zhang, Junliang Yu +3
Recommender systems (RSs) now play a very important role in the online lives of people as they serve as personalized filters for users to find relevant items from an array of optio…
Defend against advanced persistent threats: An optimal control approach
Pengdeng Li, Lu-Xing Yang, Xiaofan Yang +3
The new cyber attack pattern of advanced persistent threat (APT) has posed a serious threat to modern society. This paper addresses the APT defense problem, i.e., the problem of ho…
Maximizing the overall profit of a word-of-mouth marketing campaign: A modeling study
Pengdeng Li, Xiaofan Yang, Lu-Xing Yang +3
As compared to the traditional advertising, the word-of-mouth (WOM) communications have striking advantages such as significantly lower cost and rapid delivery; this is especially…