65 citations · 101 across the 10 of their papers we have counts for
10 papers
Diffusion-based Negative Sampling on Graphs for Link Prediction
Trung-Kien Nguyen, Yuan Fang
Link prediction is a fundamental task for graph analysis with important applications on the Web, such as social network analysis and recommendation systems, etc. Modern graph link…
Estimating Propensity for Causality-based Recommendation without Exposure Data
Zhongzhou Liu, Yuan Fang, Min Wu
Causality-based recommendation systems focus on the causal effects of user-item interactions resulting from item exposure (i.e., which items are recommended or exposed to the user)…
Voucher Abuse Detection with Prompt-based Fine-tuning on Graph Neural Networks
Zhihao Wen, Yuan Fang, Yihan Liu +2
Voucher abuse detection is an important anomaly detection problem in E-commerce. While many GNN-based solutions have emerged, the supervised paradigm depends on a large quantity of…
Augmenting Low-Resource Text Classification with Graph-Grounded Pre-training and Prompting
Zhihao Wen, Yuan Fang
Text classification is a fundamental problem in information retrieval with many real-world applications, such as predicting the topics of online articles and the categories of e-co…
Tackling the infinite likelihood problem when fitting mixtures of shifted asymmetric Laplace distributions
Yuan Fang, Brian C. Franczak, Sanjeena Subedi
Mixtures of shifted asymmetric Laplace distributions were introduced as a tool for model-based clustering that allowed for the direct parameterization of skewness in addition to lo…
GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks
Zemin Liu, Xingtong Yu, Yuan Fang +1
Graphs can model complex relationships between objects, enabling a myriad of Web applications such as online page/article classification and social recommendation. While graph neur…