157 citations · 247 across the 6 of their papers we have counts for
6 papers
Predictive Inequity in Object Detection
Benjamin Wilson, Judy Hoffman, Jamie Morgenstern
In this work, we investigate whether state-of-the-art object detection systems have equitable predictive performance on pedestrians with different skin tones. This work is motivate…
Guarantees for Spectral Clustering with Fairness Constraints
Matthäus Kleindessner, Samira Samadi, Pranjal Awasthi +1
Given the widespread popularity of spectral clustering (SC) for partitioning graph data, we study a version of constrained SC in which we try to incorporate the fairness notion pro…
Fair k-Center Clustering for Data Summarization
Matthäus Kleindessner, Pranjal Awasthi, Jamie Morgenstern
In data summarization we want to choose prototypes in order to summarize a data set. We study a setting where the data set comprises several demographic groups and we are restr…
Learning What's going on: reconstructing preferences and priorities from opaque transactions
Avrim Blum, Yishay Mansour, Jamie Morgenstern
We consider a setting where buyers, with combinatorial preferences over items, and a seller, running a priority-based allocation mechanism, repeatedly interact. Our goal, f…
Learning Valuation Distributions from Partial Observation
Avrim Blum, Yishay Mansour, Jamie Morgenstern
Auction theory traditionally assumes that bidders' valuation distributions are known to the auctioneer, such as in the celebrated, revenue-optimal Myerson auction. However, this th…
Approximately Stable, School Optimal, and Student-Truthful Many-to-One Matchings (via Differential Privacy)
Sampath Kannan, Jamie Morgenstern, Aaron Roth +1
We present a mechanism for computing asymptotically stable school optimal matchings, while guaranteeing that it is an asymptotic dominant strategy for every student to report their…