Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Information-Theoretic Bias Assessment Of Learned Representations Of
  Pretrained Face Recognition   As equality issues in the use of face recognition have garnered a lot of
attention lately, greater efforts have been made to debiased deep learning
models to improve fairness to minorities. However, there is still no clear
definition nor sufficient analysis for bias assessment metrics. We propose an
information-theoretic, independent bias assessment metric to identify degree of
bias against protected demographic attributes from learned representations of
pretrained facial recognition systems. Our metric differs from other methods
that rely on classification accuracy or examine the differences between ground
truth and predicted labels of protected attributes predicted using a shallow
network. Also, we argue, theoretically and experimentally, that logits-level
loss is not adequate to explain bias since predictors based on neural networks
will always find correlations. Further, we present a synthetic dataset that
mitigates the issue of insufficient samples in certain cohorts. Lastly, we
establish a benchmark metric by presenting advantages in clear discrimination
and small variation comparing with other metrics, and evaluate the performance
of different debiased models with the proposed metric.

24
The categories of this paper are: dg-ga
12
The categories of this paper are: nucl-th
14
The categories of this paper are: math-ph
9
The categories of this paper are: nlin
6
The categories of this paper are: astro-ph
33
The categories of this paper are: plasm-ph
31
The categories of this paper are: ao-sci
18
The categories of this paper are: econ
0
The categories of this paper are: hep-ph
28
The categories of this paper are: alg-geom
3
The categories of this paper are: physics
20
The categories of this paper are: acc-phys
2
The categories of this paper are: math
26
The categories of this paper are: bayes-an
8
The categories of this paper are: hep-ex
10
The categories of this paper are: q-bio