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cs.LG2025
FAST: Federated Active Learning with Foundation Models for Communication-efficient Sampling and Training
Haoyuan Li, Mathias Funk, Jindong Wang +1
Federated Active Learning (FAL) has emerged as a promising framework to leverage large quantities of unlabeled data across distributed clients while preserving data privacy. Howeve…
cs.LG2024
PedSleepMAE: Generative Model for Multimodal Pediatric Sleep Signals
Saurav R. Pandey, Aaqib Saeed, Harlin Lee
Pediatric sleep is an important but often overlooked area in health informatics. We present PedSleepMAE, a generative model that fully leverages multimodal pediatric sleep signals…
cs.LG2024
Collaboratively Learning Federated Models from Noisy Decentralized Data
Haoyuan Li, Mathias Funk, Nezihe Merve Gürel +1
Federated learning (FL) has emerged as a prominent method for collaboratively training machine learning models using local data from edge devices, all while keeping data decentrali…