Joint client-and-sample selection for federated learning via bi-level optimization

• Main Authors: Li, Anran, Wang, Guangjing, Hu, Ming, Sun, Jianfei, Zhang, Lan, Tuan, Luu Anh, Yu, Han
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2024
• Subjects: Computer and Information Science; Bi-level optimization; Federated learning
• Online Access: https://hdl.handle.net/10356/181061
• Institution: Nanyang Technological University

Federated Learning (FL) enables massive local data owners to collaboratively train a deep learning model without disclosing their private data. The importance of local data samples from various data owners to FL models varies widely. This is exacerbated by the presence of noisy data that exhibit lar...