Fair Classification without Sensitive Attribute Access

Excited for our next session on Hyper-Parameter Tuning for Fair Classification without Sensitive Attributes Access.

In many Financial settings, we deal with dataset with imbalance classes. Training and fine-tuning on such data requires delicate approaches to upkeep model fairness.

This month's paper is a SOTA work on the subject, a joint work by NYU, University of Maryland College Park and JPMorgan AI Research teams:
https://arxiv.org/abs/2302.01385

Looking forward to another engaging session!