3 papers
cs.LG2026
Temperature Scaling Attack Disrupting Model Confidence in Federated Learning
Kichang Lee, Jaeho Jin, JaeYeon Park +2
Predictive confidence serves as a foundational control signal in mission-critical systems, directly governing risk-aware logic such as escalation, abstention, and conservative fall…
cs.LG2025
Toward Storage-Aware Learning with Compressed Data An Empirical Exploratory Study on JPEG
Kichang Lee, Songkuk Kim, JaeYeon Park +1
On-device machine learning is often constrained by limited storage, particularly in continuous data collection scenarios. This paper presents an empirical study on storage-aware le…
cs.LG2025
FedUNet: A Lightweight Additive U-Net Module for Federated Learning with Heterogeneous Models
Beomseok Seo, Kichang Lee, JaeYeon Park
Federated learning (FL) enables decentralized model training without sharing local data. However, most existing methods assume identical model architectures across clients, limitin…