Federated Learning with Noisy User Feedback. (arXiv:2205.03092v1 [cs.LG])

Machine Learning (ML) systems are getting increasingly popular, and drive
more and more applications and services in our daily life. This has led to
growing concerns over user privacy, since human interaction data typically
needs to be transmitted to the cloud in order to train and improve such
systems. Federated learning (FL) has recently emerged as a method for training
ML models on edge devices using sensitive user data and is seen as a way to
mitigate concerns over data …

arxiv federated learning feedback learning user feedback