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Found 5 papers, 2 papers with code
Simplistic Collection and Labeling Practices Limit the Utility of Benchmark Datasets for Twitter Bot Detection
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.
Algorithms and Learning for Fair Portfolio Design
We consider a variation on the classical finance problem of optimal portfolio design.
Equilibrium Characterization for Data Acquisition Games
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.
Fair Algorithms for Learning in Allocation Problems
We formalize this fairness notion for allocation problems and investigate its algorithmic consequences.
Strategic Classification from Revealed Preferences
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.
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