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20222025
most citedEnd-to-End Learning for Stochastic Optimization: A Bayesian Perspective

4 citations · 8 across the 5 of their papers we have counts for

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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…

cs.LG2022★ 3 cited

Metrizing Fairness

Yves Rychener, Bahar Taskesen, Daniel Kuhn

We study supervised learning problems that have significant effects on individuals from two demographic groups, and we seek predictors that are fair with respect to a group fairnes…