… In this section, we propose a personalization approach for federated learning and analyze
its statistical properties. Following the statistical learning theory, in a federated learning setting …

… non-iid issue in federated learning. FedAP is extensible and … , a personalized federated
learning algorithm via adaptive … and security, and learn personalized models for each client. 2) …

… in federated learning (FL) is the … Federated learning with Adaptive Local Aggregation (FedALA)
by capturing the desired information in the global model for client models in personalized …

… We introduce an innovative approach to personalized federated learning. Our method, based
on layer-wise Fisher information values, allows for dynamic personalization that surpasses …

… We find that pFedGate can learn meaningful sparse local models adapted to different data
distributions, and conduct extensive experiments to study the effect of sparsity and verify the …

… In Federated Learning, we aim to train models across … , we study a personalized variant of
the federated learning in which … propose an adaptive federated learning algorithm that learns …

… of Federated Learning (FL), the leading paradigm for the training of machine learning models
… In this survey, we explore the domain of personalized FL (PFL) to address the fundamental …

… Federated learning (FL) has shown great promise in recent … federated learning from a
client-centric or personalized perspective. We aim to enable stronger performance on personalized …

… personalization aspect of cross-silo FL for non-IID data. We propose Adaptive Personalized
Cross-Silo Federated Learning … novel personalized cross-silo federated learning framework …

… In Federated Learning, we aim to train models across … , we study a personalized variant of
the federated learning in which … propose an adaptive federated learning algorithm that learns …