Researchers at Shanghai Polytechnic University have developed CDAFIM, a class-difficulty-aware incentive mechanism that uses Shapley values to fairly reward federated...

Researchers have developed pFedDS, a personalized federated learning approach that measures each model parameter's sensitivity to non-uniform data and adapts...

Researchers in Morocco have integrated federated learning with the OneM2M IoT service layer, showing faster, privacy-preserving machine learning at the...

Researchers at Marmara University have designed a Mutex-based sequential federated learning architecture that enables full fine-tuning of TinyLlama-1.1B on resource-constrained...

Researchers have developed FedML-DKD, a federated learning framework that uses Earth Mover's Distance to adaptively balance knowledge distillation and meta-learning,...

Researchers in India have developed ASHA, a federated learning algorithm that weights each client's updates by a dynamic contribution score,...

A new open-source simulator called FLInterrupt makes sudden client dropouts a controllable experimental variable in federated learning research, revealing how...

A new federated learning framework called FedCAMP-IDS detects known and zero-day cyberattacks across heterogeneous IoT networks with up to 99.16...

A new blockchain-enabled federated learning framework called IoV BCFL+ detects intrusions across connected vehicle networks with over 96 percent accuracy...

Researchers have developed FedDeepRiskNet++, a federated learning framework that combines differential privacy, homomorphic encryption and adaptive scheduling to let hospitals...