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cs.LG2024
Vertical Federated Learning with Missing Features During Training and Inference
Pedro Valdeira, Shiqiang Wang, Yuejie Chi
Vertical federated learning trains models from feature-partitioned datasets across multiple clients, who collaborate without sharing their local data. Standard approaches assume th…
cs.LG2024
Communication-efficient Vertical Federated Learning via Compressed Error Feedback
Pedro Valdeira, João Xavier, Cláudia Soares +1
Communication overhead is a known bottleneck in federated learning (FL). To address this, lossy compression is commonly used on the information communicated between the server and…