Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: FairNeuron: Improving Deep Neural Network Fairness with Adversary Games
  on Selective Neurons   With Deep Neural Network (DNN) being integrated into a growing number of
critical systems with far-reaching impacts on society, there are increasing
concerns on their ethical performance, such as fairness. Unfortunately, model
fairness and accuracy in many cases are contradictory goals to optimize. To
solve this issue, there has been a number of work trying to improve model
fairness by using an adversarial game in model level. This approach introduces
an adversary that evaluates the fairness of a model besides its prediction
accuracy on the main task, and performs joint-optimization to achieve a
balanced result. In this paper, we noticed that when performing backward
propagation based training, such contradictory phenomenon has shown on
individual neuron level. Based on this observation, we propose FairNeuron, a
DNN model automatic repairing tool, to mitigate fairness concerns and balance
the accuracy-fairness trade-off without introducing another model. It works on
detecting neurons with contradictory optimization directions from accuracy and
fairness training goals, and achieving a trade-off by selective dropout.
Comparing with state-of-the-art methods, our approach is lightweight, making it
scalable and more efficient. Our evaluation on 3 datasets shows that FairNeuron
can effectively improve all models' fairness while maintaining a stable
utility.

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The categories of this paper are: hep-ph
29
The categories of this paper are: funct-an
4
The categories of this paper are: cond-mat
13
The categories of this paper are: quant-ph
24
The categories of this paper are: dg-ga
25
The categories of this paper are: patt-sol
36
The categories of this paper are: cmp-lg
23
The categories of this paper are: solv-int
31
The categories of this paper are: ao-sci
16
The categories of this paper are: stat
19
The categories of this paper are: eess
9
The categories of this paper are: nlin
11
The categories of this paper are: hep-lat
21
The categories of this paper are: adap-org
18
The categories of this paper are: econ
10
The categories of this paper are: q-bio