Current federated learning algorithms take tens of communication rounds transmitting
unwieldy model weights under ideal circumstances and hundreds when data is poorly …

Federated learning (FL) is one of many tasks facilitated by crowdsourcing. Generally in such
a setting, participating workers cooperate to train a comprehensive model by exchanging the …

Model averaging is a widely adopted technique in federated learning (FL) that aggregates
multiple client models to obtain a global model. Remarkably, model averaging in FL yields a …

The unceasing development of Machine Learning (ML) and the evolution of DeepLearning
have revolutionized many application domains, ranging from natural language processing …

The field of autonomous driving is moving faster than ever, thanks to deep learning (DL)
techniques. As most research focuses on technical perspectives such as perception and …