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cs.LG2026
Cost Efficient Fairness Audit Under Partial Feedback
Nirjhar Das, Mohit Sharma, Praharsh Nanavati +2
We study the problem of auditing the fairness of a given classifier under partial feedback, where true labels are available only for positively classified individuals, (e.g., loan…
cs.LG2025
On Optimal Steering to Achieve Exact Fairness
Mohit Sharma, Amit Jayant Deshpande, Chiranjib Bhattacharyya +1
To fix the 'bias in, bias out' problem in fair machine learning, it is important to steer feature distributions of data or internal representations of Large Language Models (LLMs)…
cs.LG2024
How Far Can Fairness Constraints Help Recover From Biased Data?
Mohit Sharma, Amit Deshpande
A general belief in fair classification is that fairness constraints incur a trade-off with accuracy, which biased data may worsen. Contrary to this belief, Blum & Stangl (2019) sh…