3 papers
cs.LG2024
Election of Collaborators via Reinforcement Learning for Federated Brain Tumor Segmentation
Muhammad Irfan Khan, Elina Kontio, Suleiman A. Khan +1
Federated learning (FL) enables collaborative model training across decentralized datasets while preserving data privacy. However, optimally selecting participating collaborators i…
cs.LG2024
Recommender Engine Driven Client Selection in Federated Brain Tumor Segmentation
Muhammad Irfan Khan, Elina Kontio, Suleiman A. Khan +1
This study presents a robust and efficient client selection protocol designed to optimize the Federated Learning (FL) process for the Federated Tumor Segmentation Challenge (FeTS 2…
cs.LG2023
Regularized Weight Aggregation in Networked Federated Learning for Glioblastoma Segmentation
Muhammad Irfan Khan, Mohammad Ayyaz Azeem, Esa Alhoniemi +3
In federated learning (FL), the global model at the server requires an efficient mechanism for weight aggregation and a systematic strategy for collaboration selection to manage an…