Shannon's sampling theory and its variants provide effective solutions to the problem of reconstructing a signal from its samples in some "shift-invariant" space, wh...
Sathish Ramani, Dimitri Van De Ville, Thierry Blu,...
We study a new class of decentralized algorithms for discrete optimization via simulation, which is inspired by the fictitious play algorithm applied to games with identical inte...
We study power control in multicell CDMA wireless networks as a team optimization problem where each mobile attains at the minimum its individual fixed target SIR level and beyon...
Tansu Alpcan, Xingzhe Fan, Tamer Basar, Murat Arca...
We investigate asymptotically optimal keyword auctions, that is, auctions which maximize revenue as the number of bidders grows. We do so under two alternative behavioral assumpti...
This paper takes the first steps towards designing incentive compatible mechanisms for hierarchical decision making problems involving selfish agents. We call these Stackelberg p...