The Effect of Model Compression on Fairness in Facial Expression Recognition. (arXiv:2201.01709v1 [cs.CV])

Deep neural networks have proved hugely successful, achieving human-like
performance on a variety of tasks. However, they are also computationally
expensive, which has motivated the development of model compression techniques
which reduce the resource consumption associated with deep learning models.
Nevertheless, recent studies have suggested that model compression can have an
adverse effect on algorithmic fairness, amplifying existing biases in machine
learning models. With this project we aim to extend those studies to the
context of facial expression recognition. To …

arxiv compression cv fairness