We use techniques from sample-complexity in machine learning to reduce problems of incentive-compatible mechanism design to standard algorithmic questions, for a wide variety of r...
Maria-Florina Balcan, Avrim Blum, Jason D. Hartlin...
Recent work on online auctions for digital goods has explored the role of optimal stopping theory — particularly secretary problems — in the design of approximately optimal on...
Mohammad Taghi Hajiaghayi, Robert D. Kleinberg, Tu...
: We study the design of mechanisms in combinatorial auction domains. We focus on settings where the auction is repeated, motivated by auctions for licenses or advertising space. W...
In most mechanism design settings, optimal general-purpose mechanisms are not known. Thus the automated design of mechanisms tailored to specific instances of a decision scenario...
We initiate the study of mechanisms with verification for one-parameter agents. We give an algorithmic characterization of such mechanisms and show that they are provably better ...
Vincenzo Auletta, Roberto De Prisco, Paolo Penna, ...