fair machine learning

Responsible Machine Learning via Mixed-Integer Optimization

  • Nathan Justin
  • Qingshi Sun
  • Andrés Gómez
  • Phebe Vayanos
    • Categories Applications - OR and Management Sciences, Integer Programming, Optimization in Data Science Tags , , , , , ,

    In the last few decades, Machine Learning (ML) has achieved significant success across domains ranging from healthcare, sustainability, and the social sciences, to criminal justice and finance. But its deployment in increasingly sophisticated, critical, and sensitive areas affecting individuals, the groups they belong to, and society as a whole raises critical concerns around fairness, transparency … Read more

    The Sharpe predictor for fairness in machine learning

  • Suyun Liu
  • Luis Nunes Vicente
    • Categories Convex and Nonsmooth Optimization, Multi-Criteria Optimization, Stochastic Programming Tags , , , ,

    In machine learning (ML) applications, unfair predictions may discriminate against a minority group. Most existing approaches for fair machine learning (FML) treat fairness as a constraint or a penalization term in the optimization of a ML model, which does not lead to the discovery of the complete landscape of the trade-offs among learning accuracy and … Read more