4 citations · 13 across the 6 of their papers we have counts for
6 papers
Welfare and Fairness Dynamics in Federated Learning: A Client Selection Perspective
Yash Travadi, Le Peng, Xuan Bi +2
Federated learning (FL) is a privacy-preserving learning technique that enables distributed computing devices to train shared learning models across data silos collaboratively. Exi…
Distribution-Invariant Differential Privacy
Xuan Bi, Xiaotong Shen
Differential privacy is becoming one gold standard for protecting the privacy of publicly shared data. It has been widely used in social science, data science, public health, infor…
Improving Sales Forecasting Accuracy: A Tensor Factorization Approach with Demand Awareness
Xuan Bi, Gediminas Adomavicius, William Li +1
Due to accessible big data collections from consumers, products, and stores, advanced sales forecasting capabilities have drawn great attention from many companies especially in th…
Dynamic Tensor Recommender Systems
Yanqing Zhang, Xuan Bi, Niansheng Tang +1
Recommender systems have been extensively used by the entertainment industry, business marketing and the biomedical industry. In addition to its capacity of providing preference-ba…
Individualized Multilayer Tensor Learning with An Application in Imaging Analysis
Xiwei Tang, Xuan Bi, Annie Qu
This work is motivated by multimodality breast cancer imaging data, which is quite challenging in that the signals of discrete tumor-associated microvesicles (TMVs) are randomly di…
Multilayer tensor factorization with applications to recommender systems
Xuan Bi, Annie Qu, Xiaotong Shen
Recommender systems have been widely adopted by electronic commerce and entertainment industries for individualized prediction and recommendation, which benefit consumers and impro…