Enforcing Individual Fairness in AI Models Through Reweighting and Tuning

This work introduces a new technique called Individual Fairness through Reweighting and Tuning (IFRT) to enhance individual fairness in AI models. The proposed method defines a graph Laplacian regularizer independently on the source and target data, overcoming limitations of prior work that assumed access to the target data during training.