arXiv · 2306.04400
A Fair Classifier Embracing Triplet Collapse
Abstract
In this paper, we study the behaviour of the triplet loss and show that it can be exploited to limit the biases created and perpetuated by machine learning models. Our fair classifier uses the collapse of the triplet loss when its margin is greater than the maximum distance between two points in the latent space, in the case of stochastic triplet selection.
Explore related subjects
Keep this discovery
A. Martzloff, N. Posocco, Q. Ferré. 2023-06-07. A Fair Classifier Embracing Triplet Collapse. https://arxiv.org/abs/2306.04400
Cite the original work for its findings. Save a collection to share your selection of sources.