1 code implementation • 24 Mar 2022 • Thomas Kehrenberg, Myles Bartlett, Viktoriia Sharmanska, Novi Quadrianto
We investigate a scenario in which the absence of certain data is linked to the second level of a two-level hierarchy in the data.
no code implementations • 1 Jan 2021 • Thomas Kehrenberg, Viktoriia Sharmanska, Myles Scott Bartlett, Novi Quadrianto
In a statistical notion of algorithmic fairness, we partition individuals into groups based on some key demographic factors such as race and gender, and require that some statistics of a classifier be approximately equalized across those groups.
1 code implementation • ECCV 2020 • Thomas Kehrenberg, Myles Bartlett, Oliver Thomas, Novi Quadrianto
We propose to learn invariant representations, in the data domain, to achieve interpretability in algorithmic fairness.
Ranked #1 on Image Classification on CelebA 64x64
1 code implementation • 12 Oct 2018 • Thomas Kehrenberg, Zexun Chen, Novi Quadrianto
The issue of fairness in machine learning models has recently attracted a lot of attention as ensuring it will ensure continued confidence of the general public in the deployment of machine learning systems.
no code implementations • 10 Jan 2018 • Gil Keren, Maximilian Schmitt, Thomas Kehrenberg, Björn Schuller
Neural network models that are not conditioned on class identities were shown to facilitate knowledge transfer between classes and to be well-suited for one-shot learning tasks.