81 citations · 85 across the 4 of their papers we have counts for
4 papers
DiffsFormer: A Diffusion Transformer on Stock Factor Augmentation
Yuan Gao, Haokun Chen, Xiang Wang +4
Machine learning models have demonstrated remarkable efficacy and efficiency in a wide range of stock forecasting tasks. However, the inherent challenges of data scarcity, includin…
Studying the Impact of Data Disclosure Mechanism in Recommender Systems via Simulation
Ziqian Chen, Fei Sun, Yifan Tang +3
Recently, privacy issues in web services that rely on users' personal data have raised great attention. Unlike existing privacy-preserving technologies such as federated learning a…
Interactive Recommender System via Knowledge Graph-enhanced Reinforcement Learning
Sijin Zhou, Xinyi Dai, Haokun Chen +5
Interactive recommender system (IRS) has drawn huge attention because of its flexible recommendation strategy and the consideration of optimal long-term user experiences. To deal w…
Deep Reinforcement Learning based Recommendation with Explicit User-Item Interactions Modeling
Feng Liu, Ruiming Tang, Xutao Li +5
Recommendation is crucial in both academia and industry, and various techniques are proposed such as content-based collaborative filtering, matrix factorization, logistic regressio…