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cs.LG2026
Soft-Radial Projection for Constrained End-to-End Learning
Philipp J. Schneider, Daniel Kuhn
Integrating hard constraints into deep learning is essential for safety-critical systems. Yet existing constructive layers that project predictions onto constraint boundaries face…
cs.LG2025
Global Group Fairness in Federated Learning via Function Tracking
Yves Rychener, Daniel Kuhn, Yifan Hu
We investigate group fairness regularizers in federated learning, aiming to train a globally fair model in a distributed setting. Ensuring global fairness in distributed training p…