… both federated learning and machine learning approaches to improve inventory management.
Federated learning is an innovative approach … database cluster layer make up this system. …

… by full overlapping attribute skew between clients in Federated Learning (FL), a local … on
the images data set in the client before training begins. Next, the client calculates the mean and …

… Federated learning related researches were adopted in areas … Federated learning concept
was introduced into three … of federated learning and compared the federated learning with …

… Communication-efficient federated learning for wireless edge intelligence in IoT[J]. IEEE …
clustering-based and reliable trust-aware QoS prediction approach for cloud service …

… 同时,针对 MEC 赋能大规模无线网络中的隐私保护问题,本文 提出了一种基于联邦学习(FL,
federated learning… Improved clustering and resource allocation for ultra-dense networks[J]. China …

… By clustering the vehicle terminals covered by multiple edge … Federated learning client
selection mechanism under system … Conference on Computer Supported Cooperative Work in …

… 深度神经网络框架有联邦学习(federated learning, FL)[82],它… learning inference on
resource-constrained iot edge clusters [… : federated learning via MEC-enabled blockchain network …

… 为应对上述两个问题, 联邦学习(federated learning) 应运而生. 联邦学习, 又名联盟学习或联合
学习, 是一种由多 个客户端和一个聚合服务器参与的分布式机器学习架构. 客户端既可以是个人的…

… learning provides a new choice for high-efficiency flow scheduling. Hence,machine learning
… Finally, as the geo-distributed machine learning and federated learning become important …