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Fair Data Repair for Model Bias Reduction by nicholasliao23 is a document available to read on EtoBox.
What is Fair Data Repair for Model Bias Reduction about?
The paper presents a data repair algorithm aimed at mitigating contextual bias in datasets used for training deep neural networks (DNNs). By utilizing the coefficient of variation, the proposed method curates fair subsets of data that enhance model performance while reducing bias related to co-occurring classes. The authors demonstrate the effectiveness of their approach through experiments in both supervised and unsupervised settings, showing improved fairness in model predictions without compromising accu
- Author
- nicholasliao23
- Language
- EN