626 citations · 2.7k across the 64 of their papers we have counts for
9 papers · 1 filter
An Empirical Study on Learning Fairness Metrics for COMPAS Data with Human Supervision
Hanchen Wang, Nina Grgic-Hlaca, Preethi Lahoti +2
The notion of individual fairness requires that similar people receive similar treatment. However, this is hard to achieve in practice since it is difficult to specify the appropri…
DADI: Dynamic Discovery of Fair Information with Adversarial Reinforcement Learning
Michiel A. Bakker, Duy Patrick Tu, Humberto Riverón Valdés +4
We introduce a framework for dynamic adversarial discovery of information (DADI), motivated by a scenario where information (a feature set) is used by third parties with unknown ob…
Minimizing Margin of Victory for Fair Political and Educational Districting
Ana-Andreea Stoica, Abhijnan Chakraborty, Palash Dey +1
In many practical scenarios, a population is divided into disjoint groups for better administration, e.g., electorates into political districts, employees into departments, student…
Incremental Fairness in Two-Sided Market Platforms: On Smoothly Updating Recommendations
Gourab K Patro, Abhijnan Chakraborty, Niloy Ganguly +1
Major online platforms today can be thought of as two-sided markets with producers and customers of goods and services. There have been concerns that over-emphasis on customer sati…
Operationalizing Individual Fairness with Pairwise Fair Representations
Preethi Lahoti, Krishna P. Gummadi, Gerhard Weikum
We revisit the notion of individual fairness proposed by Dwork et al. A central challenge in operationalizing their approach is the difficulty in eliciting a human specification of…
The Price of Local Fairness in Multistage Selection
Vitalii Emelianov, George Arvanitakis, Nicolas Gast +2
The rise of algorithmic decision making led to active researches on how to define and guarantee fairness, mostly focusing on one-shot decision making. In several important applicat…