… In Section 3, we derive fast generalization bounds. In Section 4, we go beyond the bounded
… related work on the generalization analysis of heterogeneous federated learning. Finally, …

… federated learning and provide the first state-of-the-art and symmetric survey on the generalization
… -party interest in federated learning, including hundreds of papers in this fast-growing …

… machine learning … its generalization ability to unknown target data (eg, a new user). In this
paper, we incorporate the problem of Domain Generalization (DG) into Federated Learning to …

… model’s lack of generalization capacity to the sharpness of … of the loss surface and the
generalization gap, we show that i… substantially improve generalization in Federated Learning and …

… aims to achieve domain generalization without the above information leakage. … Federated
Adversarial Domain Generalization (FedADG) scheme to address the domain generalization …

… comparison with existing federated learning algorithms and … stability across various machine
learning tasks and datasets. … successful generalization on FOLB in federated learning with …

… Thus generalization studies in federated learning should … for realistic simulations of
generalization in federated learning. We … community suggestions for future federated learning …

… Thus, we argue it is of crucial importance to maintain the diversity of generalization … faster
model convergence. In this paper, we propose a novel concept called clustered generalization (…

… In this paper, we give an affirmative answer to the above question by proposing a faster …
adaptive gradient method into federated learning. We propose a faster stochastic adaptive FL …

… , a fast generalization and personalization learning method for CLIP in federated learning…
It can achieve personalization for participating clients and its remarkable generalization …