1 code implementation • 17 Jan 2023 • Chris Hays, Zachary Schutzman, Manish Raghavan, Erin Walk, Philipp Zimmer
These tools employ machine learning and often achieve near perfect performance for classification on existing datasets, suggesting bot detection is accurate, reliable and fit for use in downstream applications.
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.
no code implementations • 22 Oct 2017 • Jinshuo Dong, Aaron Roth, Zachary Schutzman, Bo Waggoner, Zhiwei Steven Wu
We study an online linear classification problem, in which the data is generated by strategic agents who manipulate their features in an effort to change the classification outcome.