4 papers
Data-Free Client Contribution Estimation via Logit Maximization for Federated Learning
Asim Ukaye, Nurbek Tastan, Mubarak Abdu-Aguye +1
Federated learning (FL) enables collaborative learning of computer vision models, where privacy and regulatory constraints prevent centralizing data across devices or organizations…
Data-Free Contribution Estimation in Federated Learning using Gradient von Neumann Entropy
Asim Ukaye, Mubarak Abdu-Aguye, Nurbek Tastan +1
Client contribution estimation in Federated Learning is necessary for identifying clients' importance and for providing fair rewards. Current methods often rely on server-side vali…
FIVA: Federated Inverse Variance Averaging for Universal CT Segmentation with Uncertainty Estimation
Asim Ukaye, Numan Saeed, Karthik Nandakumar
Different CT segmentation datasets are typically obtained from different scanners under different capture settings and often provide segmentation labels for a limited and often dis…
Introducing SDICE: An Index for Assessing Diversity of Synthetic Medical Datasets
Mohammed Talha Alam, Raza Imam, Mohammad Areeb Qazi +2
Advancements in generative modeling are pushing the state-of-the-art in synthetic medical image generation. These synthetic images can serve as an effective data augmentation metho…