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Kevin Stangl : Fairness in Machine Learning in Two Contexts: Biased Data and Pipelines.

Posted by Karoline Dubin , part of the Computer Science Theory Seminar.

At
March 16, 2022, 3 p.m.
In
612 SEO
Abstract
In this talk, I will discuss two theoretical models that capture two essential fairness in machine learning problems: the fairness-accuracy tradeoff with biased data and fairness in pipelines.