Abstract: Distributed machine learning is an effective method to alleviate intensive computation costs of training; however it suffers from network bottlenecks while gathering local results. Recent ...
Abstract: Federated learning (FL) is a privacy-preserving alternative to centralized machine learning, where model training is performed on local devices and only global model updates are shared, ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results