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cs.DC2023
Federated Learning While Providing Model as a Service: Joint Training and Inference Optimization
Pengchao Han, Shiqiang Wang, Yang Jiao +1
While providing machine learning model as a service to process users' inference requests, online applications can periodically upgrade the model utilizing newly collected data. Fed…
cs.LG2023★ 1 cited
FedAL: Black-Box Federated Knowledge Distillation Enabled by Adversarial Learning
Pengchao Han, Xingyan Shi, Jianwei Huang
Knowledge distillation (KD) can enable collaborative learning among distributed clients that have different model architectures and do not share their local data and model paramete…
cs.GT2023
Incentive Mechanism Design for Distributed Ensemble Learning
Chao Huang, Pengchao Han, Jianwei Huang
Distributed ensemble learning (DEL) involves training multiple models at distributed learners, and then combining their predictions to improve performance. Existing related studies…