31 citations · 53 across the 18 of their papers we have counts for
4 papers · 1 filter
Scaling Unsupervised Multi-Source Federated Domain Adaptation through Group-Wise Discrepancy Minimization
Larissa Reichart, Cem Ata Baykara, Ali Burak Ünal +2
Unsupervised multi-source domain adaptation (UMDA) leverages labeled data from multiple source domains to generalize to an unlabeled target. While federated UMDA addresses privacy…
Accurate and Private Diagnosis of Rare Genetic Syndromes from Facial Images with Federated Deep Learning
Ali Burak Ünal, Cem Ata Baykara, Peter Krawitz +1
Machine learning has shown promise in facial dysmorphology, where characteristic facial features provide diagnostic clues for rare genetic disorders. GestaltMatcher, a leading fram…
Federated Learning for Epileptic Seizure Prediction Across Heterogeneous EEG Datasets
Cem Ata Baykara, Saurav Raj Pandey, Ali Burak Ünal +2
Developing accurate and generalizable epileptic seizure prediction models from electroencephalography (EEG) data across multiple clinical sites is hindered by patient privacy regul…
Accelerating Targeted Hard-Label Adversarial Attacks in Low-Query Black-Box Settings
Arjhun Swaminathan, Mete Akgün
Deep neural networks for image classification remain vulnerable to adversarial examples -- small, imperceptible perturbations that induce misclassifications. In black-box settings,…