2 citations · 2 across the 1 of their papers we have counts for
2 papers
cs.CV2026★ 2 cited
Efficiently Assemble Normalization Layers and Regularization for Federated Domain Generalization
Khiem Le, Long Ho, Cuong Do +2
Domain shift is a formidable issue in Machine Learning that causes a model to suffer from performance degradation when tested on unseen domains. Federated Domain Generalization (Fe…
cs.LG2024
Exploring the Practicality of Federated Learning: A Survey Towards the Communication Perspective
Khiem Le, Nhan Luong-Ha, Manh Nguyen-Duc +3
Federated Learning (FL) is a promising paradigm that offers significant advancements in privacy-preserving, decentralized machine learning by enabling collaborative training of mod…