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FAIROD: Fairness-aware Outlier Detection [article]

Shubhranshu Shekhar, Neil Shah, Leman Akoglu
2020 arXiv   pre-print
Further, guided by our desiderata, we propose FairOD, a fairness-aware outlier detector, which has the following, desirable properties: FairOD (1) does not employ disparate treatment at test time, (2)  ...  Fairness and Outlier Detection (OD) are closely related, as it is exactly the goal of OD to spot rare, minority samples in a given population.  ...  FAIRNESS-AWARE OUTLIER DETECTION In this section, we describe our proposed FairOD -an unsupervised, fairness-aware, end-to-end OD model that embeds our proposed learnable (i.e. optimizable) fairness constraints  ... 
arXiv:2012.03063v1 fatcat:rvmzpyade5dudn5hkk3dkf3cfm

Anomaly Mining – Past, Present and Future [article]

Leman Akoglu
2021 arXiv   pre-print
The outlier mining community has recently routed attention to fairness-aware detection.  ...  , and (4) fairness-aware OD.  ... 
arXiv:2105.10077v2 fatcat:znvvz6ewpbdpjhnhp35kudvzlu

Outlier Detection using AI: A Survey [article]

Md Nazmul Kabir Sikder, Feras A. Batarseh
2021 arXiv   pre-print
It is important to detect outlier events as carefully as possible to avoid infrastructure failures because anomalous events can cause minor to severe damage to infrastructure.  ...  Accordingly, and due to its variability, Outlier Detection (OD) is an ever-growing research field. In this chapter, we discuss the progress of OD methods using AI techniques.  ...  For model assurance, in recent study, Shekhar et al. (2020) applied a novel framework based on deepautoencoder for fairness called Fairness-aware OD (FairOD).  ... 
arXiv:2112.00588v1 fatcat:yonfnhohpnbxxgiwrxon74mcny

Anomaly Mining - Past, Present and Future

Leman Akoglu
2021 Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence   unpublished
The outlier mining community has recently routed attention to fairness-aware detection.  ...  Fairness-aware Outlier Detection Fair data mining and OD are close cousins, as it is exactly the goal of OD to spot rare, minority samples in the data.  ... 
doi:10.24963/ijcai.2021/697 fatcat:ob6us4ek3vbandwmqpv3jtwioe