56 citations · 104 across the 6 of their papers we have counts for
5 papers · 1 filter
On the Impact of Multi-dimensional Local Differential Privacy on Fairness
Karima Makhlouf, Heber H. Arcolezi, Sami Zhioua +2
Automated decision systems are increasingly used to make consequential decisions in people's lives. Due to the sensitivity of the manipulated data as well as the resulting decision…
Shedding light on underrepresentation and Sampling Bias in machine learning
Sami Zhioua, Rūta Binkytė
Accurately measuring discrimination is crucial to faithfully assessing fairness of trained machine learning (ML) models. Any bias in measuring discrimination leads to either amplif…
Identifiability of Causal-based Fairness Notions: A State of the Art
Karima Makhlouf, Sami Zhioua, Catuscia Palamidessi
Machine learning algorithms can produce biased outcome/prediction, typically, against minorities and under-represented sub-populations. Therefore, fairness is emerging as an import…
Survey on Causal-based Machine Learning Fairness Notions
Karima Makhlouf, Sami Zhioua, Catuscia Palamidessi
Addressing the problem of fairness is crucial to safely use machine learning algorithms to support decisions with a critical impact on people's lives such as job hiring, child malt…
Machine learning fairness notions: Bridging the gap with real-world applications
Karima Makhlouf, Sami Zhioua, Catuscia Palamidessi
Fairness emerged as an important requirement to guarantee that Machine Learning (ML) predictive systems do not discriminate against specific individuals or entire sub-populations,…