4 citations · 9 across the 7 of their papers we have counts for
3 papers · 1 filter
EvoFed: Leveraging Evolutionary Strategies for Communication-Efficient Federated Learning
Mohammad Mahdi Rahimi, Hasnain Irshad Bhatti, Younghyun Park +2
Federated Learning (FL) is a decentralized machine learning paradigm that enables collaborative model training across dispersed nodes without having to force individual nodes to sh…
NEO-KD: Knowledge-Distillation-Based Adversarial Training for Robust Multi-Exit Neural Networks
Seokil Ham, Jungwuk Park, Dong-Jun Han +1
While multi-exit neural networks are regarded as a promising solution for making efficient inference via early exits, combating adversarial attacks remains a challenging problem. I…
StableFDG: Style and Attention Based Learning for Federated Domain Generalization
Jungwuk Park, Dong-Jun Han, Jinho Kim +3
Traditional federated learning (FL) algorithms operate under the assumption that the data distributions at training (source domains) and testing (target domain) are the same. The f…