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Beyond Static Classification: Long-term Fairness for Minority Groups via Performative Prediction and Distributionally Robust Optimization
DownloadFall 2022
In recent years machine learning (ML) models have begun to be deployed at enormous scales, but too often without adequate concern for whether or not an ML model will make fair decisions. Fairness in ML is a burgeoning research area, but work to define formal fairness criteria has some serious...
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Fall 2021
A great deal of statistical research has been done in high- and ultrahigh-dimensional settings in recent years. Regularized approaches have been extensively used in dealing with high-dimensional datasets. It is widely acknowledged that robust procedures are important to deal with the influence of...