Abstract: This paper proposes the use of causal modeling to detect and mitigate algorithmic bias. We provide a brief description of causal modeling and a general overview of our approach. We then use ...
Abstract: In highly imbalanced binary classification tasks with asymmetric misclassification costs, traditional cost-insensitive learning strategies fail to reflect true risk and often yield poor ...
ABSTRACT: Automatic detection of cognitive distortions from short written text could support large-scale mental-health screening and digital cognitive-behavioural therapy (CBT). Many recent approaches ...
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