Web: http://arxiv.org/abs/2206.07801

June 17, 2022, 1:10 a.m. | Wael Alghamdi, Hsiang Hsu, Haewon Jeong, Hao Wang, P. Winston Michalak, Shahab Asoodeh, Flavio P. Calmon

cs.LG updates on arXiv.org arxiv.org

We consider the problem of producing fair probabilistic classifiers for
multi-class classification tasks. We formulate this problem in terms of
"projecting" a pre-trained (and potentially unfair) classifier onto the set of
models that satisfy target group-fairness requirements. The new, projected
model is given by post-processing the outputs of the pre-trained classifier by
a multiplicative factor. We provide a parallelizable iterative algorithm for
computing the projected classifier and derive both sample complexity and
convergence guarantees. Comprehensive numerical comparisons with
state-of-the-art benchmarks …

arxiv fairness lg prediction

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