3 papers
cs.LG2026
Multimodal Federated Learning under Dual-Axis Modality Missingness
Adiba Orzikulova, Jaehyun Kwak, Jaemin Shin +5
Multimodal federated learning (FL) supports collaborative modeling in privacy-sensitive health-sensing and medical settings, but realistic deployments often exhibit dual-axis modal…
cs.LG2024
Federated Learning for Time-Series Healthcare Sensing with Incomplete Modalities
Adiba Orzikulova, Jaehyun Kwak, Jaemin Shin +1
Many healthcare sensing applications utilize multimodal time-series data from sensors embedded in mobile and wearable devices. Federated Learning (FL), with its privacy-preserving…
cs.LG2024
(FL): Overcoming Few Labels in Federated Semi-Supervised Learning
Seungjoo Lee, Thanh-Long V. Le, Jaemin Shin +1
Federated Learning (FL) is a distributed machine learning framework that trains accurate global models while preserving clients' privacy-sensitive data. However, most FL approaches…