3 papers
cs.AI2026
SleepMaMi: A Universal Sleep Foundation Model for Integrating Macro- and Micro-structures
Keondo Park, Younghoon Na, Yourim Choi +3
While the shift toward unified foundation models has revolutionized many deep learning domains, sleep medicine remains largely restricted to task-specific models that focus on loca…
cs.LG2026
Let the Void Be Void: Robust Open-Set Semi-Supervised Learning via Selective Non-Alignment
You Rim Choi, Subeom Park, Seojun Heo +2
Open-set semi-supervised learning (OSSL) leverages unlabeled data containing both in-distribution (ID) and unknown out-of-distribution (OOD) samples, aiming simultaneously to impro…
cs.LG2024
Effective Heterogeneous Federated Learning via Efficient Hypernetwork-based Weight Generation
Yujin Shin, Kichang Lee, Sungmin Lee +3
While federated learning leverages distributed client resources, it faces challenges due to heterogeneous client capabilities. This necessitates allocating models suited to clients…