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Hybrid processing for algorithmic fairness
20 décembre 2022 ThèseAlgorithmic decisions are currently being used on a daily basis. These decisions often rely on Machine Learning (ML) algorithms that may produce complex and opaque ML models. Recent studies raised unfairness concerns by revealing discriminating outcomes produced by ML models against minorities and unprivileged group… -
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Making ML models fairer through explanations: the case of LimeOut
15 octobre 2020 Communication dans un congrèsAlgorithmic decisions are now being used on a daily basis, and based on Machine Learning (ML) processes that may be complex and biased. This raises several concerns given the critical impact that biased decisions may have on individuals or on society as a whole. Not only unfair outcomes affect human rights, they als…