12 citations · 12 across the 8 of their papers we have counts for
Showing 2025 · cs.LGShow all
3 papers · 2 filters
cs.LG2025
When to Stop Federated Learning: Zero-Shot Generation of Synthetic Validation Data with Generative AI for Early Stopping
Youngjoon Lee, Hyukjoon Lee, Jinu Gong +2
Federated Learning (FL) enables collaborative model training across decentralized devices while preserving data privacy. However, FL methods typically run for a predefined number o…
cs.LG2025
Adaptive Token-Weighted Differential Privacy for LLMs: Not All Tokens Require Equal Protection
Manjiang Yu, Priyanka Singh, Xue Li +1
Large language models (LLMs) frequently memorize sensitive or personal information, raising significant privacy concerns. Existing variants of differential privacy stochastic gradi…
cs.LG2025
Debunking Optimization Myths in Federated Learning for Medical Image Classification
Youngjoon Lee, Hyukjoon Lee, Jinu Gong +2
Federated Learning (FL) is a collaborative learning method that enables decentralized model training while preserving data privacy. Despite its promise in medical imaging, recent F…