no code implementations • 2 Oct 2023 • Hadi Elzayn, Emily Black, Patrick Vossler, Nathanael Jo, Jacob Goldin, Daniel E. Ho
Unlike similar existing approaches, our methods take advantage of contextual information -- specifically, the relationships between a model's predictions and the probabilistic prediction of protected attributes, given the true protected attribute, and vice versa -- to provide tighter bounds on the true disparity.
no code implementations • 20 Jun 2022 • Emily Black, Hadi Elzayn, Alexandra Chouldechova, Jacob Goldin, Daniel E. Ho
First, we show how the use of more flexible machine learning (classification) methods -- as opposed to simpler models -- shifts audit burdens from high to middle-income taxpayers.
no code implementations • 10 Mar 2021 • Hadi Elzayn, Riccardo Colini-Baldeschi, Brian Lan, Okke Schrijvers
This paper studies equilibrium quality of semi-separable position auctions (known as the Ad Types setting) with greedy or optimal allocation combined with generalized second-price (GSP) or Vickrey-Clarke-Groves (VCG) pricing.
Computer Science and Game Theory
1 code implementation • 12 Jun 2020 • Emily Diana, Travis Dick, Hadi Elzayn, Michael Kearns, Aaron Roth, Zachary Schutzman, Saeed Sharifi-Malvajerdi, Juba Ziani
We consider a variation on the classical finance problem of optimal portfolio design.
no code implementations • 22 May 2019 • Jinshuo Dong, Hadi Elzayn, Shahin Jabbari, Michael Kearns, Zachary Schutzman
We demonstrate a reduction from this potentially complicated action space to a one-shot, two-action game in which each firm only decides whether or not to buy the data.
no code implementations • 30 Aug 2018 • Hadi Elzayn, Shahin Jabbari, Christopher Jung, Michael Kearns, Seth Neel, Aaron Roth, Zachary Schutzman
We formalize this fairness notion for allocation problems and investigate its algorithmic consequences.