4 papers · 1 filter
OCT-FedSIR: Toward Trustworthy Federated Ophthalmic Learning under Annotation Noise
Sina Gholami, Abdulmoneam Ali, Tania Haghighi +8
Federated learning enables collaborative model development without centralizing patient data, but annotation reliability at participating institutions cannot always be assumed. In…
Eigenspace-Based Clustering for Personalized System Identification
Abdulmoneam Ali, Dipankar Maity, Ahmed Arafa
We study the problem of system identification in heterogeneous settings, where different systems may follow distinct underlying dynamics. Existing clustered system identification a…
FedSIR: Spectral Client Identification and Relabeling for Federated Learning with Noisy Labels
Sina Gholami, Abdulmoneam Ali, Tania Haghighi +2
Federated learning (FL) enables collaborative model training without sharing raw data; however, the presence of noisy labels across distributed clients can severely degrade the lea…
FB-NLL: A Feature-Based Approach to Tackle Noisy Labels in Personalized Federated Learning
Abdulmoneam Ali, Ahmed Arafa
Personalized Federated Learning (PFL) aims to learn multiple task-specific models rather than a single global model across heterogeneous data distributions. Existing PFL approaches…