67 citations · 96 across the 8 of their papers we have counts for
4 papers · 1 filter
How Low Can You Go? Practical cold-start performance limits in FaaS
Yue Tan, David Liu, Nanqinqin Li +1
Function-as-a-Service (FaaS) has recently emerged as a new cloud computing paradigm. It promises high utilization of data center resources through allocating resources on demand at…
Federated Learning for Privacy-Preserving Open Innovation Future on Digital Health
Guodong Long, Tao Shen, Yue Tan +3
Privacy protection is an ethical issue with broad concern in Artificial Intelligence (AI). Federated learning is a new machine learning paradigm to learn a shared model across user…
Federated Learning for Open Banking
Guodong Long, Yue Tan, Jing Jiang +1
Open banking enables individual customers to own their banking data, which provides fundamental support for the boosting of a new ecosystem of data marketplaces and financial servi…
FedProto: Federated Prototype Learning across Heterogeneous Clients
Yue Tan, Guodong Long, Lu Liu +4
Heterogeneity across clients in federated learning (FL) usually hinders the optimization convergence and generalization performance when the aggregation of clients' knowledge occur…