194 citations · 998 across the 36 of their papers we have counts for
5 papers · 1 filter
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…
Private Pareto Optimal Exchange
Sampath Kannan, Jamie Morgenstern, Ryan Rogers +1
We consider the problem of implementing an individually rational, asymptotically Pareto optimal allocation in a barter-exchange economy where agents are endowed with goods and have…
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…
Privacy-Preserving Public Information for Sequential Games
Avrim Blum, Jamie Morgenstern, Ankit Sharma +1
In settings with incomplete information, players can find it difficult to coordinate to find states with good social welfare. For example, in financial settings, if a collection of…