IEEE

Batch-Aggregate: Efficient Aggregation for Private Federated Learning in VANETs

Abstract: Federated learning (FL) in Vehicular Ad-hoc Networks (VANETs) enables vehicles to collaboratively train machine learning models by aggregating local gradients without revealing the training ...
IEEE

Toward Secure Weighted Aggregation for Privacy-Preserving Federated Learning

Abstract: Privacy-preserving federated learning can protect the privacy of model gradients/parameters in the model aggregation phase. Most existing schemes only ...
GitHub

fastapi-example

Practical Clean Architecture backend example built with FastAPI. No stateful globals (DI), low coupling (DIP), tactical DDD, CQRS, proper UoW usage. REST API, per ...